The present invention relates to automatic headlamp control systems for vehicles and, more particularly, to automatic headlamp control systems that automatically adjust the high and low beam states of a vehicle headlamp.
Automotive forward lighting systems are evolving in several areas including the use of image-based sensors, typically referred to as Automatic High Beam (AHB) control systems, to maximize the use of high beam road illumination when appropriate, the use of steerable beam systems, typically referred to as Adaptive Front Lighting (AFL) systems, to provide a greater range of beam pattern options particularly for driving on curved roads or during turn maneuvers wherein the beam pattern may be biased or supplemented in the direction of the curve or turn, and the combination of such AHB and AFL systems.
U.S. Pat. No. 6,097,023 (which is hereby incorporated herein by reference in its entirety) describes an automatic high beam control system which utilizes an optical system, an image sensor, and signal processing including spectral, spatial and temporal techniques to determine ambient lighting conditions, the road environment, and the presence of other road users in order to automatically control the selection of the appropriate forward lighting state such that user forward vision is optimized while minimizing the impact of headlamp caused glare on other road users in all lighting conditions.
While AHB systems that utilize the features and concepts described within the above identified U.S. patent have achieved performance levels that have resulted in considerable commercial success, it is desired to provide additional features and techniques, which may increase the utility, improve the performance, facilitate the manufacture, and simplify the installation of such systems.
The present invention provides an automatic headlamp control system that is operable to automatically control or adjust the high beam state of a vehicle's headlamps. The headlamp control system is operable to spread out or de-focus a captured image to spread out the imaging of a light source so that an image of a distant light source is captured by at least two pixels of an image array sensor. The image array sensor thus may receive at least a portion of the light source (which may be a red tail light of a leading vehicle) on a red sensing pixel to enhance early detection of the distance tail light. The headlamp control system may provide enhanced control of the headlamps when the vehicle is driven around curves or bends in the road and may be operable in response to a steering wheel angle of the vehicle. The headlamp control system may be adjustable to align the optical axis of the imaging system with a vehicle axis in response to detection of light sources and tracking of movement of the light sources as the vehicle travels along the road.
These and other objects, advantages, purposes and features of the present invention will become apparent upon review of the following specification in conjunction with the drawings.
In order to facilitate the description of features and enhancements, some specific configurations, to be reviewed in conjunction with the drawings, is described below. It will be understood that the components and values described are for illustrative purposes and do not limit the scope of the disclosed invention.
With reference to
The optical system 12 is held by features of the housing assembly 18 in a constrained spatial relationship with the image sensor 13, such that an optical system axis 17 is perpendicular to the active plane of the image sensor 13 and passes generally through its center point, and such that the distance between the optical system 12 and the image sensor 13 may be adjusted to bring the optical system focal plane into a predetermined relationship with the active plane of the image sensor 13 during the manufacturing process and thereafter locked in position. The housing assembly may utilize aspects of the modules or assemblies described in U.S. Pat. Nos. 6,968,736; 6,877,888; 6,824,281; 6,690,268; 6,672,744; 6,593,565; 6,516,664; 6,501,387; 6,428,172; 6,386,742; 6,341,523; 6,329,925; 6,326,613; 6,250,148 and 6,124,886, and/or U.S. patent application Ser. No. 10/456,599, filed Jun. 6, 2003, now U.S. Pat. No. 7,004,593; Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018, and/or Ser. No. 11/201,661, filed Aug. 11, 2005, now U.S. Pat. No. 7,480,149, and/or PCT Application No. PCT/US03/40611, filed Dec. 19, 2003; PCT Application No. PCT/US03/03012, filed Jan. 31, 2003, and/or PCT Application No. PCT/US04/15424, filed May 18, 2004, and/or Ireland patent applications, Ser. No. S2004/0614, filed Sep. 15, 2004; Ser. No. S2004/0838, filed Dec. 14, 2004; and Ser. No. S2004/0840, filed Dec. 15, 2004, which are all hereby incorporated herein by reference in their entireties.
The accessory module or housing assembly 18 includes an outer housing 18a that is removably attached to an attachment plate 19, which is fixedly attached to the upper central region of the inside surface of the vehicle's windshield 20 such that the optical system axis 17 is substantially horizontal and substantially parallel to the vehicle's principal central axis. Preferably, the housing assembly 18 is positioned at the windshield such that the light rays that pass through the optical system 12 to the image sensor 13 also pass through a portion of the vehicle's windshield swept by the vehicle's windshield wiper system.
As shown in
The image sensor 13 is preferably, but not limited to, a CMOS photosensor array, such as part number MT9V125 produced by Micron Corporation, with 640 rows and 480 columns of 5.6 micron square photosensor elements and circuitry to measure the quantity of photons that impinge each photosensor element during a controllable period of time. In the described configuration, the image sensor is oriented such that the 640 photosensor rows are horizontal and the 480 columns are vertical. Thus, in combination with the optical system 12, the image sensor 13 has about a 48 degree horizontal field of view and about a 36 degree vertical field of view.
In order to extract color information from the image or image data, one of a number of filter types, each able to transmit a particular band of wavelength, covers the active surface of each of the photosensor elements of the array. The most commonly used color filter pattern, and therefore the most economically available as a standard feature of a commercially available image sensor, is the Bayer pattern in which either a blue, green or red pass filter is applied to the surface of each of the image sensor photosensor elements, such as shown in
Optionally, the imaging device or module may comprise an imaging or intelligent headlamp control (IHC) module. For example, an intelligent headlamp control module may have a dimensionally small cavity around a lens holder 132 (
In order to accommodate the crush ribs, several lens modifications may be needed, since a typical existing lens often has threads which may bind in the crush ribs. Thus, in order to accommodate the crush ribs, the lens may be manufactured or modified to have a smooth bore in order to engage the control surfaces of the ribs evenly along the barrel of the lens holder.
The crush rib feature of the lens holder secures the lens during manufacture. However, it is desirable to apply an adhesive at the lens holder and lens to substantially permanently attach the lens to the plastic barrel of the lens holder. Lateral grooves around the barrel of the lens may be provided to allow the flow of adhesive around the lens for a more uniform lens attachment or securement. Such grooves do not interfere with the crush ribs during insertion as much as threads would and allow the flow of adhesive greater than a substantially smooth bore.
In order to control alignment and precision of the insertion of the lens down the barrel (toward and away from the imager), a gripper may be provided to isolate the head of the lens between two overlapping control surfaces that would hold the lens and control the toward and away (from the imager) motion during the focusing process.
The control surface of the printed circuit board (PCB) during the lens insertion process preferably facilitates several criteria, both mechanical and electrical, during such an automated process. The nest may secure the imager board and backplate simultaneously in a repeatable orientation for lens insertion. The nest may also allow for electrical attachment to the ECU by way of pogo pins or the like during the focusing process. It may also articulate in order to secure the ECU board to the backplate after the focusing process.
In order to achieve enhanced AHB control system performance, it is desirable to detect the tail lamp of a leading vehicle at about 200 meters. The minimum tail light emitting surface area to meet legal requirements is about 50 cm2, which can be achieved using about an 80 mm diameter circular or about a 71 mm square emitting surface. However, in most cases, tail lamp designs are driven by vehicle styling considerations and a desire on the part of vehicle manufacturers to exceed minimum requirements by a safe margin. Such design and styling constraints often result in tail lamp emitting surfaces with either a horizontal or vertical dimension of at least about 125 mm.
Using the above described optical system 12 and imaging array 13, each photosensor element of the array has an effective horizontal field of view FOVph and an effective vertical field of view FOVpv, where:
FOVph=FOVpv=48 degrees/640 pixels=0.075 degrees/pixel.
Thus, each photosensor element of the array subtends a region of a vertical plane at distance R meters from the imager, which measures ph by pv where:
ph=pv=FOVph×R×1000×PI/180 mm=1.309×R mm.
Thus, at a distance of about 200 m, the portion of the forward scene subtended by each photosensor element of the array measures about 262 mm by about 262 mm, which is approximately twice the dimension of a typical tail lamp of a vehicle. Since the dimension of the image of a tail lamp at about 200 meters is in the order of half that of a photosensor element, it is possible that the tail lamp image will lie entirely on the blue and green detecting photosensor elements of a 2 by 2 block of photosensor elements, and thus may result in a pixel value with no red content. In order to assure that the red content of the image of the tail lamp at about 200 meters is measured and results in a red component of the calculated pixel color value, it is desirable that the tail lamp image dimension be in the order of about one and a half times that of a photosensor element, such that no matter where it lies or is received on the photosensor array it will cover at least a portion of at least one red detecting photosensor.
This could be achieved by reducing the field of view of the optical system by a factor of about three, resulting in a horizontal field of view of about 16 degrees and a significant reduction in other aspects of system performance. It could also be achieved by increasing the number of photosensor elements in each row of the image sensor by a factor of about three, with a corresponding reduction of photosensor element dimension, or by increasing the number of photosensor elements in each row of the image sensor by a factor of about three, maintaining the photosensor element dimension, and changing the optical system specification in order to maintain about a 48 degree horizontal field of view. However, this is typically not a practical solution due to the cost or availability of such image sensors and the cost of the additional processing capacity required to handle the significantly increased amount of image data.
It is thus an aspect of the present invention to increase the effective size of the image at the image sensor of a tail lamp at 200 meters, so that its presence and color may be detected, without changing the optical system or image sensor and while maintaining the ability to perform other object detection tasks to support additional features and functions, such as described below.
The following analysis of the optical system contained within the AHB control system will serve to explain the principles used to establish an optimal configuration.
For a thin lens: 1/s+1/d=1/f (1)
or: d=f×s/(s−f)
similarly: d′=f×s′/(s′−f)
by similar triangles: C=a×(d−d′)/d′
by definition: a=f/N
by substitution: C=f2×(s′−s)/N×s′×(s−f) (2)
Consider now the object point to be replaced by a circular uniform light source of diameter D. When placed at point P, the image of the disc at the image plane would appear as a focused disc of diameter D′ with uniform intensity (such as shown at A in
Rearranging equation (1) to solve for s:
s=f×s′×(C×N+f)/(C×N×s′+f2) (3)
For the optical system described above, f=4.5 mm and N=1.8. Thus, C=0.0056 mm, s′=200 m, and s=1.933 m. Thus, the same amount of light energy has been distributed over a greater image area. By focusing the lens to focus an image of an object P that is about 1.993 m from the lens, the defocused object P′ at about 200 m from the lens will be defocused to have a diameter that will allow the image to be received by more than one pixel of the imaging array sensor or camera. Such an expanded image of the light source (by de-focusing the image of an object at about 200 meters) will be received by more than one pixel and will be at least partially received by a red sensing pixel so that the system can determine whether or not a distant light source is a red light source and thus whether or not the distant light source may be a taillight of a leading vehicle.
Focusing or adjustment of the lens may be performed via any suitable focusing means, such as a linear slide mechanism that has a high resolution motor and controller, such as an MX-80 miniature slide with a Vix 250 IM motion controller commercially available from Parker-Hannifin. Such as slide mechanism and motor may provide a resolution of about 1 μm and a repeatability of about 2 μm or thereabouts. Such characteristics make good resolution possible across the focus range so that the captured image data will illustrate or approximate an enhanced or optimum focus value.
Once an image was loaded by the software, the image may be analyzed by many different means including line profiles and color analysis. For the processing of the image data, a processor system or software, such as Data Translation's DT Vision Foundry©, may be used to analyze the images using software masks or regions of interest (ROI's). The exemplary DT Vision Foundry© software provides an imaging software designed to assist machine vision systems in operation, programming, and data management.
The imaging software was used to process image ROI's using a line profile tool. The line profile tool examines the pixel gain values which the line mask lays. The line profile tool graphically illustrates the gain values across the mask. It also may provide a data export tool which enables the user to view and manipulate the intensity values gathered from the imager.
Imager color values are independent to a color pixel. Four pixels in a grid pattern, as shown in
The first method of compression is to get the maximum pixel value from the green pixels in the quad. The second green pixel in the quad is set to the maximum green pixel's value. This method works well in most applications. However, since focus is directly related to the sharpness of the edges of the target in an image, the green pixel values should not be extended to allow the edge to appear sharper than it is. As shown by the edges B and C in
While some visual resolution may be lost by averaging the green pixels, for matters of image processing the data is typically more telling. If the target image edge falls on the imager, such as edge B or C of
Focus is directly related to the sharpness of the edges of the target image. Optionally, two image processing tools may be used: a histogram and a line profile. After image data are captured and stored, the automatic focus software processes the image data with a histogram tool. A histogram of a region of interest (ROI) in an image will illustrate, using a bar graph, the number of pixels at their respective intensity value. The theory behind using a histogram is that as a black and white target image is processed, a more focused image would have more pixels in extremes and fewer pixels in the medium intensity range. However, in order to create an algorithm to focus the imager, a more perceivable pattern to predict the focal distance was needed.
Optionally, and desirably, the intelligent headlamp control (IHC) may focus by capturing individual picture frames and measuring a line profile through a target image consisting of several dark bars separated by different spacing. After finding the line profiles across the target, the slope of the line profiles is calculated to find the sharpness of the edges of the target image. If the target image is sharp (in focus), the peak of the slope will be abrupt and large. If the edges of the target image are blurry, the peak of the slope will be smaller and less abrupt (as can be seen with reference to
Thus, a line profile tool may be implemented to examine the pixels in a one dimensional mask or line. Such a line profile tool charts the intensity values detected by the imager along the line mask, such as shown in
To find the slope, the intensity value of the pixels in the line profile can be calculated in several ways. However, in order to simplify the calculation, the following method to find slope was derived:
Once the slope had been determined by the above equation, the maximum and minimum slopes from that image were recorded along with the reference distance away from the starting back focal length as shown in
After the slope of the line profile has been plotted, the slope can be plotted against the back focal distance by finding the maximum and minimum slope. As shown in
After creating several “Slope vs. Distance” curves, the tolerance range for the back focal distance may be approximately ±100 microns from nominal. The tolerance specification given for the lens may be ±210 microns. These tolerance stack-ups require an individual focus for each lens to imager combination.
Using the same line profile slope plot as in
The software design of the automated focus system is a closed loop software controlled system that utilizes the focus curve as shown in
Since a single line profile may allow for failure in the above process, many line profiles are preferably examined and averaged in order to effectively focus a lens to an imager in a production setting. However, the single line profile used in experimentation exhibits the predictability and repeatability of the focal length curve.
Thus, the software needed to control the auto-focus system should accomplish three things: (1) control the imager; (2) calculate image data; and (3) control the slide table for adjustment. In order to control the imager, the digital video signal from the imager may be coming in through USB, and the software may capture individual frames for calculation upon command. The software also may be capable of reading and writing exposure and gain values for image capture.
The GUI must be able to interactively place and store multiple line ROI's in order to take measurements across the image. Line profiles that correlate with the line ROI's are calculated to find the measure of focus at that specific position. The derivative of each line profile is taken in order to find the slope of the line profile. After these calculations are complete for one image, the peak slopes from each line profile will be averaged together. This number will be compared to a stored table that the program will be able to access in order to find the approximate distance (number of steps) away from nominal focus. After the nominal focus has been reached by means of line profile, the GUI is able to calculate histograms from multiple rectangular ROI's. These histograms may reveal the percentage of data between the two peaks of the histograms, and the control may average that percentage to give a validation to the line profile. The software and control are further able to either virtually or physically interface to the slide controller package in order to input distances and command operations to the slide controller.
After completing several iterations of the focus experiment, several conclusions were made. The target design should have a white object on a black background with angled edges by which line profiles and histograms may discern a sharp focused edge. The histogram method of detecting focus was adequate for detecting focus. However, this method required the motion control to step through many increments of focal length until the histogram criteria reached acceptable limits. Although this method would be adequate and relatively simple to implement, the line profile method revealed a more calculable and immediate pattern of focus.
The line profile method of measuring focus is readily chartable and predictable across the focal distance range. However, although the boundary region between a white and black target may be readily examined, whereby the sharpness of the target is only measured at that point in the target image, more line profiles may be needed to be performed across the image for real-world or non black and white target applications.
Thus, the mathematical algorithm and the curve data methodology discussed above may be implemented as a focus algorithm for present and future forward facing imager systems (and optionally rearward facing imager systems and/or sideward facing imager systems and the like). Although each imager and lens combination will have its own focus curve data, the initial data collection will be a minimal component to the setup procedure. Preferably, the focus can and should be attained by going directly to a calculated focal distance processed by initial out-of-focus images captured by the imager. By using this procedure, attaining focus in a production scenario can be greatly hastened.
Real lenses do not typically focus all rays perfectly due to spherical or other aberrations, diffraction effects from wave optics and the finite aperture of the lens, resulting in an unfocused image with a circle of confusion CL, which is an essentially constant value dependent on lens quality and independent of the distance of the object or the image from the optical center of the lens. The combined effects result in a total circle of confusion CT for images received by the image sensor. Further, the magnification M of the lens is defined as the ratio of the image dimension LI to the object dimension LO. Thus, M=LI/LO.
High volume component manufacturing and assembly processes used in the production of optical systems at low cost typically result in part to part variations in their optical characteristics. Additionally, dimensional tolerances are associated with the manufacture of the housing assembly components, with the placement of the imaging array die in its package, and with the placement of the imaging array on the printed circuit board assembly.
Forward facing image capture and signal processing components, such as incorporated in the described AHB control system, may be used to obtain information regarding the location, movement and other characteristics of many objects of relevance to the driving task or operation of the vehicle within the image sensor's field of view, in order to provide additional features and functions, such as, but not limited to, traffic lane detection and lane departure warning, traffic sign recognition, traffic light status detection, fog detection, rain sensing, and/or to supplement or complement the use of other sensors or sensing technologies in the provision of other features and functions such as, but not limited to, adaptive cruise control, pre-crash sensing, pedestrian detection, etc., thus increasing the utility and value of the AHB control system and reducing the cost and space requirements associated with providing each of the features and functions as independent stand-alone systems.
In order to provide optimum detection and characterization of the wide range of objects of relevance or interest in support of the above listed features and functions, amongst others, under a wide range of lighting conditions, it is necessary to consider the requirements of each detection task or group of similar detection tasks.
Typical fixed beam forward lighting systems offer two beam patterns, low and high, with low beam preferably providing the maximum forward and lateral road illumination without causing direct glare to other oncoming or leading vehicle operators such that it may be used in all driving conditions, and high beam preferably providing the maximum forward illumination range with reduced lateral coverage to provide improved forward visibility during night driving when other road users are not present within the extended illuminated region, that is, the region in which they would be subject to glare from the vehicle's high beam headlamps.
Optionally, AHB control systems may incorporate a low speed threshold below which high beam selection is inhibited, in order to avoid activation of high beams when unnecessary, such as when driving at a speed which is safe given the forward visibility provided by the low beam lighting, or when undesirable, such as when driving on city roads.
There are, however, circumstances above this low speed threshold in which it is desirable to maintain, or switch to, a low beam state, even in the absence of other road users in the high beam illumination region. One such circumstance occurs when the vehicle is driven round a bend with a short radius of curvature. In this situation the value of the long range illumination resulting from the use of high beams is reduced since it is not aligned with the vehicle trajectory and typically illuminates off road regions. However, the wider short range beam pattern resulting from the use of low beams can provide increased illumination along the left or right hand curving vehicle trajectory.
Thus, an aspect of the present invention is to improve existing AHB control systems by inhibiting high beam selection when improved relevant road illumination may be provided by the use of low beam headlights, and in particular when the radius of curvature of the current, or instantaneous, vehicle trajectory falls below a predetermined threshold value.
The threshold value is ideally determined based on the specific high and low beam patterns generated by the lighting equipment installed on the vehicle. Additionally, since headlight beam patterns are typically asymmetric, and since the distance to the edge of the road is different when driving round a left or right hand curve, the left and right hand vehicle trajectory radius of curvature threshold values may be different.
The current or instantaneous vehicle trajectory radius of curvature may be obtained or derived from several sources, including, but not limited to steering wheel angular position. The correlation between the vehicle trajectory radius of curvature and steering wheel angular position may be readily established with knowledge of the vehicle mechanical configuration. Thus, steering wheel angular position thresholds which are substantially equivalent to vehicle trajectory radius of curvature thresholds may be derived. Typically, the current, or instantaneous, angular position of the vehicle steering wheel is measured by a rotary encoder, or equivalent sensing device, and is made available to other vehicle control systems either directly or via a vehicle communication bus such as a CAN or the like. By accessing this signal or vehicle bus message, and comparing it to a predetermined threshold, high beam activation may be inhibited to achieve the previously described benefits.
If the vehicle is driven round a long steady curve with a radius of curvature which corresponds to the steering wheel angular threshold, it is possible that the instantaneous steering wheel angular value will oscillate about the angular threshold, resulting in a potentially annoying or inappropriate oscillation between high and low beam states. Thus, the AHB control system may incorporate a time based filter, which may be adaptive, and which may be non-symmetrical, to regulate what might otherwise be frequent annoying or inappropriate switching between the low and high beam states. Depending on the characteristics of the time based filtering system, it may be beneficial to incorporate hysteresis in the angular threshold values, such that the values for left and right increasing steering wheel angles are greater than the values for left and right decreasing steering wheel angles.
Automatic image based high beam control systems (such as described in U.S. Pat. No. 6,097,023, which is hereby incorporated herein by reference in its entirety), in which an image of the scene forward of the vehicle is focused by an optical system, may have a horizontal field of view equal to, but not limited to, approximately +/−22.5 degrees about the imaging system centerline. The image may be focused or imaged onto a rectangular array image capture device such as, but not limited to, a 640×480 CMOS color imager, which captures image data and provides sequential frames of data indicative of the light energy reflected or emitted by objects in the region subtended by each element of the array. The image capture rate may be at a rate in the range of about 5 to 120 times per second or more, with processing being performed on the data to determine the presence, location and characteristics of objects within the monitored scene and to determine characteristics of the monitored scene, such as general illumination level, and to utilize several defined regions of the monitored scene for several different purposes. For example, the region of the scene which generally corresponds to the region of influence of the vehicle high beam pattern, may be used to determine the need to inhibit high beam activation if other road users are detected within that region. The regions to the left and right of the first region may be used to anticipate the upcoming entry of other road users into the first region in order to facilitate a rapid and appropriate response upon entry or just prior to entry of the first region. The upper central region of the monitored scene may be used to determine ambient lighting conditions such that a first threshold may be established below which low beam headlights are activated, and a second threshold may be established above which high beam activation may be inhibited, while the lower horizontal portion of the ambient lighting condition detection region may be used to detect urban lighting conditions or the like. Other processing of the captured image data may be implemented depending on the particular application of the image sensor and processor, while remaining within the spirit and scope of the present invention.
While the segmentation of the monitored scene into fixed regions, such as described above, provides many benefits and efficiencies to the image processing routines used to characterize vehicular light sources, ambient lighting conditions, and non-vehicular light sources etc., they only provide optimal performance when they are appropriately aligned with the monitored scene, such as when driving on a flat straight road. Much of the typical driving experience, however, is on curved and undulating roads. It is, therefore, desirable to have dynamic segmentation of the monitored scene such that the various regions employed align appropriately according to the upcoming road topology and geometry.
An additional aspect of the present invention is to improve the performance of AHB control systems by providing a dynamic segmentation of the monitored scene.
When driving on a curved road, it is beneficial to extend the region used to detect and monitor vehicular light sources in the direction of road curvature in order to provide a sufficiently early detection of other road users and thus the inhibition of high beams. This region may be extended in accordance with the vehicle trajectory radius of curvature as determined by the steering wheel angle or other means as previously described. Additionally, the upcoming road condition may be anticipated by other means, such as vehicle pitch as may be monitored by an accelerometer, combination of accelerometers or other means, such as by detection of vehicle roll, visible horizon tilt and/or yaw detection and/or in response to a GPS output or the like.
An additional aspect of the present invention is to improve the performance of AHB control systems, when used in conjunction with adaptive forward lighting (AFL) systems, by actively changing the region of high beam inhibit in response to the vehicle trajectory radius of curvature, in order that it corresponds to the current region of influence of the high beam pattern.
Typical AFL systems are responsive to the vehicle trajectory radius of curvature and provide improved road surface illumination when driving on curved roads by mechanically, or otherwise, adjusting the beam direction or providing supplementary illumination in the direction of the curve. While this provides a solution to the problem addressed above for fixed beam systems, it introduces a shortcoming for a typical fixed beam high beam control system when used to control high beam selection in an AFL system.
While the detection of leading and on-coming/approaching vehicles occurs across a wide field of view, the inhibition of high beam selection occurs in a narrower fixed region which corresponds to the region of influence of the fixed high beam pattern. When driving around a curve with an AFL system, the region of influence of the adaptive high beam pattern is extended in the direction of the curve, thus reducing the effective response time to a vehicle entering the region of high beam inhibit from the direction of the road curvature. It is, therefore advantageous to modify the region of high beam inhibit in correspondence with the modified high beam pattern.
While this may be accomplished through image processing and scene analysis, it is preferable, in order to minimize the complexity, and therefore to minimize the cost of implementation, of the image processing algorithms employed, to use a signal indicative of the vehicle trajectory radius of curvature or the AFL system beam direction control signal. As previously described, the steering wheel angle may be most conveniently used since it correlates to the vehicle trajectory radius of curvature and is commonly available from the vehicle data bus. The region of high beam inhibit may be adjusted in a continuous fashion in correspondence with the instantaneous high beam direction, or it may be adjusted in one or more steps according to one or more steering wheel angle threshold values.
An additional aspect of the present invention is to improve the performance of existing AHB control systems by improving the characterization of non-vehicular light sources when driving on curved roads.
In order to enhance AHB control system performance, it is desirable to provide accurate detection and characterization of other vehicular road users in order to assure the appropriate inhibition of high beam use. Additionally, all other light sources within the monitored scene may be characterized as non-vehicular in order to enhance or maximize forward vision by enabling high beams whenever appropriate and also to avoid the annoyance caused to the user by inappropriate returns to low beams due to the false characterization of non-vehicular light sources as vehicular sources.
Spatial, spectral and temporal techniques are typically used to aid in the appropriate characterization of light sources. It is, however, particularly challenging to correctly characterize light sources when driving round road curves which are provided with reflective signs to indicate road curvature. To achieve the greatest visibility of these signs or reflectors, they are typically located and oriented to provide the maximum possible reflection of light from the host vehicle headlights, that is, at a height above ground level which is similar to that of typical vehicle lights and oriented such that they reflect light from the headlight beams directly back towards the host vehicle as it progresses around the bend. Thus, the spectral and geometric characteristics and locations of these signs or reflectors may be similar to that of other vehicles traveling along the curve or bend in the road.
An additional aspect of the present invention is to improve the performance of existing AHB control systems by providing an automatic repeating alignment of the sensor to the vehicle centerline and the horizontal plane such that the various regions of interest within the scene monitored by the sensor are optimally maintained regardless of vehicle and high beam control system module geometric manufacturing and assembly tolerances, and other sources of misalignment such as vehicle attitude variations due to a wide range of possible vehicle loading conditions.
In order to take advantage of the environmental protection offered by the vehicle cabin, the frequently cleaned optically clear path offered by the vehicle windshield (which is cleaned or wiped by the windshield wipers when the wipers are activated), and the relatively high vantage point offered at the upper region or top of the windshield, AHB control systems are preferably mounted centrally on the upper inside surface of the front windshield of a vehicle and with a forward field of view through the region cleaned or wiped by the windshield wipers.
Typical vehicle body structures, windshields and assembly systems each contribute to the geometric tolerance associated with the surface to which the AHB control system module is attached. The module also has some degree of geometric tolerance associated with its components and assembly methods. It is not unusual to encounter a total stack up of tolerances which result in a potential vertical and horizontal misalignment of +/−2 degrees from the theoretically ideal condition. This is a significant value and may result in errors in determining lane widths and object sizes and distances and the like.
It is known to provide a mechanical adjustment means to allow for the correction of this misalignment at the installation of the AHB control system to the vehicle. This is, however, often undesirable since it often is expensive to apply manual labor to the alignment of components on each vehicle equipped with an AHB control system on the vehicle assembly line. It is additionally undesirable since the alignment procedure is subject to operator error.
Also, during the lifetime of the vehicle the windshield may be damaged and require replacement. In such an event it would be necessary, and likely at an unacceptable cost, to provide the alignment techniques, tools and equipment to every service operation that may be required to replace a windshield and remount the AHB control system module in order to return the vehicle to its original performance level.
Additionally, in normal use, a typical vehicle experiences many different loading conditions which cause it to adopt a wide range of pitch and roll attitudes, causing an AHB control system which is attached to the vehicle to view the forward scene from perspectives different from the ideal, or initially considered design condition, potentially resulting in different headlight actuation decisions than contemplated by the original system specification.
Thus, it is beneficial for an AHB control system to include a feature which automatically compensates for an initial misalignment condition and additionally is capable of correcting for temporary vehicle conditions and re-installation misalignments which may occur during the use of the vehicle.
In order to achieve optimum performance of the AHB control system, it is desirable to determine which of the array elements of the image capture device fall into each of the defined regions. Since the regions are defined relative to the forward scene, it is desirable to determine a particular point within the forward scene and to relate that point to a particular array element of the image capture device.
The particular point in the forward scene may be defined as a particular distant point which lies on the forward extended vehicle centerline on the horizontal plane which passes through the center of the optical system associated with the image capture device. When driving on a substantially flat and substantially straight road, the distant point may be the point within the forward scene at which the headlights of an oncoming vehicle or the tail lamps of a slower leading vehicle are first detected. As the distance between the host and target vehicles decreases, the image of the target vehicle expands within the imaged scene, towards the left if traveling in a leftward lane, centrally if in the same lane, and towards the right if traveling in a rightward lane. Thus the described distant point may be called the focus of expansion or FOE.
In order to determine the imaging array element or pixel which subtends the FOE in the as assembled and as loaded vehicle, it is necessary to identify the array element which first detects a new light source, which has the potential to be a vehicular source, within that region of the monitored scene which could potentially contain the FOE, to continue to track the light source as it expands in the image as the distance between the detected source and the host vehicle decreases until it is confirmed that the source is vehicular, and to monitor the host vehicle trajectory until it reaches the point in the road where the new light source would have been initially detected in order to confirm that the road traveled for the duration of the monitoring period was substantially flat and substantially straight. If it is determined that the point or light source is a vehicle and the host vehicle and approaching vehicle are traveling along a substantially flat and substantially straight road, the location of the initial distant point or FOE may be compared to an expected location and the axis of the imaging system may be adjusted accordingly so that the imaging system is directed at the desired or appropriate or optimal angle relative to the vehicle. Optionally, the imaging system may be adjusted in response to a detection of lane markers along a straight and/or flat road, and/or pitch information from a bus or accelerometer and/or roll information from an accelerometer or bus information. Optionally, the system may only monitor for new light sources when the steering wheel angle or steering angle (SA) is approximately 0 degrees, such as when the steering angle is about 0 degrees+\−0.1 degrees or other threshold angle. Thus, adjustment and/or alignment of the image sensor may occur by tracking movement of light sources through the images when the vehicle is traveling substantially straight, so that the control may compare the tracked light sources to expected locations and paths through the captured images as the vehicle moves along the substantially straight path and may adjust the field of view or viewing angle of the image sensor accordingly.
An additional aspect of the present invention is to improve AHB control systems by providing a detection of left and right hand road systems and an automatic configuration to assure appropriate left or right hand operation. AHB control systems are often installed on both left and right hand drive vehicles and may be configured differently for use on left and right hand drive road systems, preferably having an asymmetric response to activity within the monitored scene. It is possible to configure the system to operate on either a left or right hand drive vehicle and to supply the system to the vehicle assembly plant for installation on a corresponding either left or right hand drive vehicle. In such cases it is desirable to identify the AHB control system module with a particular part number in order to assure the installation of the correct configuration, which results in part number proliferation and the potential for operator error, either at the module manufacturing location where the wrong label may be attached to the product, or at the vehicle assembly plant, particularly if left and right hand drive vehicles are built on the same assembly line, where the wrong part may be selected for installation.
In order to reduce part number proliferation, it is possible to provide a switch on the AHB control system module in order to configure it for operation on a left or right hand drive vehicle. This solution, however, is also subject to operator error and may result in incorrect and inappropriate control of the vehicle high beams during nighttime driving. Additionally, during the normal use of a right hand drive vehicle, it may be driven on a left hand drive road system for a period of time before returning to a right hand drive road system and vice versa, such as when taking a vehicle by ferry or Channel tunnel from the United Kingdom to mainland Europe for vacation or in the course of business. Again it is possible to provide a switch to allow the vehicle operator to configure the system appropriately for the country of use, however, this is inconvenient and may result in inappropriate high beam activation in the event that the operator forgets to, or is unaware of the need to switch to the alternate configuration, or is unaware of the availability of a reconfiguration switch. Thus, there is a need to provide an automatic configuration of AHB control systems such that they analyze the monitored scene, recognize a left or right hand drive road system and self-configure accordingly.
The system may track the light sources and adjust the image sensor only when the steering angle is within a threshold value of straight or substantially straight, in order to avoid misinterpretation of source locations. Also, the system may take into account the environment at which the vehicle is traveling, and may not track and adjust when the vehicle is traveling in high lighting environments, such as cities and the like, and may function when there are limited other light sources in the forward field of view. The system may also take into account the speed of the vehicle and thus the speed of the light moving through the captured images.
Optionally, when the vehicle is being passed on tight curves or the like, the control may determine when to adjust the headlamps of the vehicle in response to the location and departure of the passing vehicle's taillights within the field of view. For example, the control may take into account situations when the forward vehicle departs the field of view while the steering angle of the subject vehicle remains relatively constant, and may adjust the headlamps accordingly. Such tracking may also provide an indication that the road continues to curve ahead of the subject vehicle, and may provide information useful in conjunction with an adaptive cruise control (ACC) system and/or a lane departure warning (LDW) or the like.
Adaptive Front Lighting vehicles can illuminate curved road areas and vehicles that previously were not illuminated very well. The AHBC algorithm could, at significant expense and speed penalties, decide when the vehicle was on a curve and change its operation. If the AHBC system could use steering wheel angle (SWA) from the automobile bus, it could react significantly faster, with fewer mistakes, without the calculation penalties of internal SWA calculation.
We have done several studies on how the steering wheel angle will improve AHBC functionality when used with AFLS. For example, 14 vehicles in 7 video clips which had both AFLS cars and standard cars were studied. These clips showed vehicles traveling on a curve and were examined to determine how to better detect these vehicles. The region of interest was extended manually in the direction of the curved travel. The SWA was not used during such examination and evaluation, but it is envisioned that the use of steering wheel angle would allow these results to be done automatically. Based on such evaluations, the optimum size and location of the region of interest (ROI) may be found. The ROI is the vehicle processing region. Surprisingly (and as shown in
The smaller amount of gained low beam time on a sharp curve is not to be belittled. The total time that the vehicle was visible in the imaging system on sharp curves averaged around 3-4 seconds. The addition of 0.6 seconds of low beam time is significant since these vehicle detections usually only had a couple seconds of low beam, so the added time is a significant benefit. For the gentle curves the vehicles were visible in the scene for longer, and were detected in low beam for about 1.6 seconds more, thus the added time was significant.
In the future when more target vehicles have adaptive front lighting, this effect may not be so static. Then the ROI may need to be changed as a function of the steering wheel angle. The desired approach was to extend the ROI 5 or 6 degrees in the direction of the curve denoted by the steering wheel angle. With no or small SWA, the ROI is unchanged. This approach is enough to provide significant benefit for the AHBC vehicle with AFLS. The AFLS system does point the headlights in the direction of the curve and this use of SWA will allow the quicker detection of the target vehicle so that the effect of the AFLS is minimized for other drivers. The other vehicles will not get as much unexpected glare at unexpected angles on a curve, because they will be detected sooner by the host AHBC vehicle.
Optionally, the SWA may be used to filter out the false alarm targets from reflectors and house and yard lights on curves. When the vehicle is driven along the road, the system does not know how the road curves ahead and if it did, such as through SWA, the system could better filter out such false targets. This is particularly evident when the false target is straight ahead, while the road curves. In such cases, the false target is in the same position as a real vehicle. With the use of the steering wheel angle, this false alarm can be minimized, and it is estimated that at least about a third of these kinds of false alarms could be eliminated. These also are the most resistant false alarms since they look the most like real car lights.
Finally, the use of SWA could allow us to better filter out the non-straight roads that should be ignored to adapt the focus of expansion. The system can accumulate the focus of expansion data when it detects the lane markers, and may only accumulate when the FOE is close enough to the manufacturing value. The system could better filter out these curved road times and should allow the system to get a better, quicker, measure of the real FOE for a given key cycle.
Therefore, the use of SWA will allow quicker use of low beams on curves where the AFLS system will otherwise glare opposing vehicles more than the non-AFLS vehicle. The detection time, when low beam is on, may preferably increase by about 30 percent or more. The use of SWA will also allow better filtering out of noise sources which falsely trigger low beam, and it will more quickly provide adaptive focus of expansion in general driving.
The imaging sensor for the headlamp control of the present invention may comprise any suitable sensor, and may utilize various imaging sensors or imaging array sensors or cameras or the like, such as a CMOS imaging array sensor, a CCD sensor or other sensors or the like, such as the types described in U.S. Pat. Nos. 6,946,978; 7,004,606; 5,550,677; 5,760,962; 6,097,023; 5,796,094 and/or 5,715,093; and/or U.S. patent application Ser. No. 09/441,341, filed Nov. 16, 1999, now U.S. Pat. No. 7,339,149; and/or Ser. No. 11/105,757, filed Apr. 14, 2005, now U.S. Pat. No. 7,526,103, and/or PCT Application No. PCT/US2003/036177 filed Nov. 14, 2003, published Jun. 3, 2004 as PCT Publication No. WO 2004/047421, which are all hereby incorporated herein by reference in their entireties.
Optionally, the imaging sensor may be suitable for use in connection with other vehicle imaging systems, such as, for example, a blind spot detection system, where a blind spot indicator may be operable to provide an indication to the driver of the host vehicle that an object or other vehicle has been detected in the lane or area adjacent to the side of the host vehicle. In such a blind spot detector/indicator system, the blind spot detection system may include an imaging sensor or sensors, or ultrasonic sensor or sensors, or sonar sensor or sensors or the like. For example, the blind spot detection system may utilize aspects of the blind spot detection and/or imaging systems described in U.S. Pat. Nos. 7,038,577; 6,882,287; 6,198,409; 5,929,786 and/or 5,786,772, and/or U.S. patent application Ser. No. 11/315,675, filed Dec. 22, 2005, now U.S. Pat. No. 7,720,580; and/or Ser. No. 11/239,980, filed Sep. 30, 2005, now U.S. Pat. No. 7,881,496, and/or U.S. provisional applications, Ser. No. 60/696,953, filed Jul. 6, 2006; Ser. No. 60/628,709, filed Nov. 17, 2004; Ser. No. 60/614,644, filed Sep. 30, 2004; and/or Ser. No. 60/618,686, filed Oct. 14, 2004, and/or of the reverse or backup aid systems, such as the rearwardly directed vehicle vision systems described in U.S. Pat. Nos. 5,550,677; 5,760,962; 5,670,935; 6,201,642; 6,396,397; 6,498,620; 6,717,610; 6,757,109 and/or 7,005,974, and/or of the rain sensors described in U.S. Pat. Nos. 6,250,148 and 6,341,523, and/or of other imaging systems, such as the types described in U.S. Pat. Nos. 6,353,392 and 6,313,454, and U.S. patent application Ser. No. 10/422,512, filed Apr. 24, 2003, now U.S. Pat. No. 7,123,168, with all of the above referenced U.S. patents, patent applications and provisional applications and PCT applications being commonly assigned and being hereby incorporated herein by reference.
Optionally, the mirror assembly and/or accessory module or windshield electronics module may include one or more displays, such as for displaying the captured images or video images captured by the imaging sensor or sensors of the vehicle, such as the displays of the types disclosed in U.S. Pat. Nos. 7,004,593; 5,530,240 and/or 6,329,925, which are hereby incorporated herein by reference, and/or display-on-demand or transflective type displays, such as the types disclosed in U.S. Pat. Nos. 6,690,268; 5,668,663 and/or 5,724,187, and/or in U.S. patent application Ser. No. 10/054,633, filed Jan. 22, 2002, now U.S. Pat. No. 7,195,381; Ser. No. 11/021,065, filed Dec. 23, 2004, now U.S. Pat. No. 7,255,451; Ser. No. 10/528,269, filed Mar. 17, 2005, now U.S. Pat. No. 7,274,501; Ser. No. 10/533,762, filed May 4, 2005, now U.S. Pat. No. 7,184,190; Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018; Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0061008; Ser. No. 10/993,302, filed Nov. 19, 2004, now U.S. Pat. No. 7,338,177; and/or Ser. No. 11/284,543, filed Nov. 22, 2005, now U.S. Pat. No. 7,370,983, and/or PCT Application No. PCT/US03/29776, filed Sep. 9, 2003; and/or PCT Application No. PCT/US03/35381, filed Nov. 5, 2003, and/or PCT Application No. PCT/US03/40611, filed Dec. 19, 2003, which are all hereby incorporated herein by reference, or may include or incorporate video displays or the like, such as the types described in PCT Application No. PCT/US03/40611, filed Dec. 19, 2003, and/or U.S. patent application Ser. No. 10/538,724, filed Jun. 13, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0050018; and/or Ser. No. 11/284,543, filed Nov. 22, 2005, now U.S. Pat. No. 7,370,983, and/or U.S. provisional applications, Ser. No. 60/732,245, filed Nov. 1, 2005; Ser. No. 60/759,992, filed Jan. 18, 2006; and/or Ser. No. 60/836,219, filed Aug. 8, 2006, which are hereby incorporated herein by reference.
The imaging sensor may be incorporated at or in an accessory module or windshield electronics module (such as described above), or may be incorporated at or in an interior rearview mirror assembly of the vehicle, while remaining within the spirit and scope of the present invention. Optionally, the mirror assembly and/or module may support one or more other accessories or features, such as one or more electrical or electronic devices or accessories. For example, illumination sources or lights, such as map reading lights or one or more other lights or illumination sources, such as illumination sources of the types disclosed in U.S. Pat. Nos. 6,690,268; 5,938,321; 5,813,745; 5,820,245; 5,673,994; 5,649,756; 5,178,448; 5,671,996; 4,646,210; 4,733,336; 4,807,096; 6,042,253; 6,971,775 and/or 5,669,698, and/or U.S. patent application Ser. No. 10/054,633, filed Jan. 22, 2002, now U.S. Pat. No. 7,195,381; and/or Ser. No. 10/933,842, filed Sep. 3, 2004, now U.S. Pat. No. 7,249,860, which are hereby incorporated herein by reference, may be included in the mirror assembly or module. The illumination sources and/or the circuit board may be connected to one or more buttons or inputs for activating and deactivating the illumination sources. Optionally, the mirror assembly or module may also or otherwise include other accessories, such as microphones, such as analog microphones or digital microphones or the like, such as microphones of the types disclosed in U.S. Pat. Nos. 6,243,003; 6,278,377 and/or 6,420,975, and/or in PCT Application No. PCT/US03/308877, filed Oct. 1, 2003. Optionally, the mirror assembly may also or otherwise include other accessories, such as a telematics system, speakers, antennas, including global positioning system (GPS) or cellular phone antennas, such as disclosed in U.S. Pat. No. 5,971,552, a communication module, such as disclosed in U.S. Pat. No. 5,798,688, a voice recorder, transmitters and/or receivers, such as for a garage door opener or a vehicle door unlocking system or the like (such as a remote keyless entry system), a digital network, such as described in U.S. Pat. No. 5,798,575, a memory mirror system, such as disclosed in U.S. Pat. No. 5,796,176, a hands-free phone attachment, a video device for internal cabin surveillance (such as for sleep detection or driver drowsiness detection or the like) and/or video telephone function, such as disclosed in U.S. Pat. Nos. 5,760,962 and/or 5,877,897, a remote keyless entry receiver, a seat occupancy detector, a remote starter control, a yaw sensor, a clock, a carbon monoxide detector, status displays, such as displays that display a status of a door of the vehicle, a transmission selection (4wd/2wd or traction control (TCS) or the like), an antilock braking system, a road condition (that may warn the driver of icy road conditions) and/or the like, a trip computer, a tire pressure monitoring system (TPMS) receiver (such as described in U.S. Pat. Nos. 6,124,647; 6,294,989; 6,445,287; 6,472,979 and/or 6,731,205; and/or U.S. patent application Ser. No. 11/232,324, filed Sep. 21, 2005, now U.S. Pat. No. 7,423,522, and/or an ONSTAR® system and/or any other accessory or circuitry or the like (with all of the above-referenced patents and PCT and U.S. patent applications being commonly assigned, and with the disclosures of the referenced patents and patent applications being hereby incorporated herein by reference in their entireties).
Optionally, the mirror assembly or module may include one or more user inputs for controlling or activating/deactivating one or more electrical accessories or devices of or associated with the mirror assembly or module or vehicle. The mirror assembly or module may comprise any type of switches or buttons, such as touch or proximity sensing switches, such as touch or proximity switches of the types described in PCT Application No. PCT/US03/40611, filed Dec. 19, 2003; and/or U.S. Pat. Nos. 6,001,486; 6,310,611; 6,320,282 and 6,627,918; and/or U.S. patent application Ser. No. 09/817,874, filed Mar. 26, 2001, now U.S. Pat. No. 7,224,324; Ser. No. 10/956,749, filed Oct. 1, 2004, now U.S. Pat. No. 7,446,924; Ser. No. 10/933,842, filed Sep. 3, 2004, now U.S. Pat. No. 7,249,860; Ser. No. 11/021,065, filed Dec. 23, 2004, now U.S. Pat. No. 7,255,451; and/or Ser. No. 11/140,396, filed May 27, 2005, now U.S. Pat. No. 7,360,932, which are hereby incorporated herein by reference, or the inputs may comprise other types of buttons or switches, such as those described in U.S. patent application Ser. No. 11/029,695, filed Jan. 5, 2005, now U.S. Pat. No. 7,253,723; and/or Ser. No. 11/451,639, filed Jun. 13, 2006, now U.S. Pat. No. 7,527,403, which are hereby incorporated herein by reference, or such as fabric-made position detectors, such as those described in U.S. Pat. Nos. 6,504,531; 6,501,465; 6,492,980; 6,452,479; 6,437,258 and 6,369,804, which are hereby incorporated herein by reference. Other types of switches or buttons or inputs or sensors may be incorporated to provide the desired function, without affecting the scope of the present invention.
Optionally, the user inputs or buttons may comprise user inputs for a garage door opening system, such as a vehicle based garage door opening system of the types described in U.S. Pat. Nos. 6,396,408; 6,362,771 and 5,798,688, and/or U.S. patent application Ser. No. 10/770,736, filed Feb. 3, 2004, now U.S. Pat. No. 7,023,322; and/or U.S. provisional applications, Ser. No. 60/502,806, filed Sep. 12, 2003; and Ser. No. 60/444,726, filed Feb. 4, 2003, which are hereby incorporated herein by reference. The user inputs may also or otherwise function to activate and deactivate a display or function or accessory, and/or may activate/deactivate and/or commence a calibration of a compass system of the mirror assembly and/or vehicle. The compass system may include compass sensors and circuitry within the mirror assembly or within a compass pod or module at or near or associated with the mirror assembly. Optionally, the user inputs may also or otherwise comprise user inputs for a telematics system of the vehicle, such as, for example, an ONSTAR® system as found in General Motors vehicles and/or such as described in U.S. Pat. Nos. 4,862,594; 4,937,945; 5,131,154; 5,255,442; 5,632,092; 5,798,688; 5,971,552; 5,924,212; 6,243,003; 6,278,377; 6,420,975; 6,946,978; 6,477,464; 6,678,614 and/or 7,004,593, and/or U.S. patent application Ser. No. 10/645,762, filed Aug. 20, 2003, now U.S. Pat. No. 7,167,796; and Ser. No. 10/964,512, filed Oct. 13, 2004, now U.S. Pat. No. 7,308,341; and/or PCT Application No. PCT/US03/40611, filed Dec. 19, 2003, and/or PCT Application No. PCT/US03/308877, filed Oct. 1, 2003, which are all hereby incorporated herein by reference.
Optionally, the accessory module may utilize aspects of other accessory modules or windshield electronics modules or the like, such as the types described in U.S. patent application Ser. No. 10/958,087, filed Oct. 4, 2004, now U.S. Pat. No. 7,188,963; and/or Ser. No. 11/201,661, filed Aug. 11, 2005, now U.S. Pat. Nos. 7,480,149, and/or 7,004,593; 6,824,281; 6,690,268; 6,250,148; 6,341,523; 6,593,565; 6,428,172; 6,501,387; 6,329,925 and 6,326,613, and/or in PCT Application No. PCT/US03/40611, filed Dec. 19, 2003, and/or Ireland patent applications, Ser. No. S2004/0614, filed Sep. 15, 2004; Ser. No. S2004/0838, filed Dec. 14, 2004; and Ser. No. S2004/0840, filed Dec. 15, 2004, which are all hereby incorporated herein by reference.
The reflective element of the rearview mirror assembly of the vehicle may comprise an electro-optic or electrochromic reflective element or cell, such as an electrochromic mirror assembly and electrochromic reflective element utilizing principles disclosed in commonly assigned U.S. Pat. Nos. 6,690,268; 5,140,455; 5,151,816; 6,178,034; 6,154,306; 6,002,544; 5,567,360; 5,525,264; 5,610,756; 5,406,414; 5,253,109; 5,076,673; 5,073,012; 5,117,346; 5,724,187; 5,668,663; 5,910,854; 5,142,407 and/or 4,712,879, and/or U.S. patent application Ser. No. 10/054,633, filed Jan. 22, 2002, now U.S. Pat. No. 7,195,381; Ser. No. 11/021,065, filed Dec. 23, 2004, now U.S. Pat. No. 7,255,451; Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0061008, and/or PCT Application No. PCT/US2006/018567, filed May 15, 2006, which are all hereby incorporated herein by reference, and/or as disclosed in the following publications: N. R. Lynam, “Electrochromic Automotive Day/Night Mirrors”, SAE Technical Paper Series 870636 (1987); N. R. Lynam, “Smart Windows for Automobiles”, SAE Technical Paper Series 900419 (1990); N. R. Lynam and A. Agrawal, “Automotive Applications of Chromogenic Materials”, Large Area Chromogenics: Materials and Devices for Transmittance Control, C. M. Lampert and C. G. Granquist, EDS., Optical Engineering Press, Wash. (1990), which are hereby incorporated by reference herein. The thicknesses and materials of the coatings on the substrates of the electrochromic reflective element, such as on the third surface of the reflective element assembly, may be selected to provide a desired color or tint to the mirror reflective element, such as a blue colored reflector, such as is known in the art and/or such as described in U.S. Pat. Nos. 5,910,854 and 6,420,036, and in PCT Application No. PCT/US03/29776, filed Sep. 9, 2003, which are all hereby incorporated herein by reference.
Optionally, use of an elemental semiconductor mirror, such as a silicon metal mirror, such as disclosed in U.S. Pat. Nos. 6,286,965; 6,196,688; 5,535,056; 5,751,489 and 6,065,840, and/or in U.S. patent application Ser. No. 10/993,302, filed Nov. 19, 2004, now U.S. Pat. No. 7,338,177, which are all hereby incorporated herein by reference, can be advantageous because such elemental semiconductor mirrors (such as can be formed by depositing a thin film of silicon) can be greater than 50 percent reflecting in the photopic (SAE J964a measured), while being also substantially transmitting of light (up to 20 percent or even more). Such silicon mirrors also have the advantage of being able to be deposited onto a flat glass substrate and to be bent into a curved (such as a convex or aspheric) curvature, which is also advantageous since many passenger-side exterior rearview mirrors are bent or curved.
Optionally, the reflective element may include a perimeter metallic band, such as the types described in PCT Application No. PCT/US03/29776, filed Sep. 19, 2003; and/or PCT Application No. PCT/US03/35381, filed Nov. 5, 2003; and/or U.S. patent application Ser. No. 11/021,065, filed Dec. 23, 2004, now U.S. Pat. No. 7,255,451; and/or Ser. No. 11/226,628, filed Sep. 14, 2005 and published Mar. 9, 2006 as U.S. Publication No. US-2006-0061008, which are hereby incorporated herein by reference. Optionally, the reflective element may include indicia formed at and viewable at the reflective element, such as by utilizing aspects of the reflective elements described in PCT Application No. PCT/US2006/018567, filed May 15, 2006, which are hereby incorporated herein by reference.
Optionally, the reflective element of the mirror assembly may comprise a single substrate with a reflective coating at its rear surface, without affecting the scope of the present invention. The mirror assembly thus may comprise a prismatic mirror assembly or other mirror having a single substrate reflective element, such as a mirror assembly utilizing aspects described in U.S. Pat. Nos. 6,318,870; 6,598,980; 5,327,288; 4,948,242; 4,826,289; 4,436,371 and 4,435,042; and PCT Application No. PCT/US04/015424, filed May 18, 2004; and U.S. patent application Ser. No. 10/933,842, filed Sep. 3, 2004, now U.S. Pat. No. 7,249,860, which are hereby incorporated herein by reference. Optionally, the reflective element may comprise a conventional prismatic or flat reflective element or prism, or may comprise a prismatic or flat reflective element of the types described in PCT Application No. PCT/US03/29776, filed Sep. 19, 2003; U.S. patent application Ser. No. 10/709,434, filed May 5, 2004, now U.S. Pat. No. 7,420,756; Ser. No. 10/933,842, filed Sep. 3, 2004, now U.S. Pat. No. 7,249,860; Ser. No. 11/021,065, filed Dec. 23, 2004, now U.S. Pat. No. 7,255,451; and/or Ser. No. 10/993,302, filed Nov. 19, 2004, now U.S. Pat. No. 7,338,177, and/or PCT Application No. PCT/US2004/015424, filed May 18, 2004, which are all hereby incorporated herein by reference, without affecting the scope of the present invention.
Changes and modifications to the specifically described embodiments may be carried out without departing from the principles of the present invention, which is intended to be limited by the scope of the appended claims, as interpreted in accordance with the principles of patent law.
The present application is a continuation of U.S. patent application Ser. No. 17/814,577, filed Jul. 25, 2022, now U.S. Pat. No. 11,623,559, which is a continuation of U.S. patent application Ser. No. 17/451,183, filed Oct. 18, 2021, now U.S. Pat. No. 11,396,257, which is a continuation of U.S. patent application Ser. No. 16/948,656, filed Sep. 28, 2020, now U.S. Pat. No. 11,148,583, which is a continuation of U.S. patent application Ser. No. 16/125,891, filed Sep. 10, 2018, now U.S. Pat. No. 10,787,116, which is a continuation of U.S. patent application Ser. No. 15/262,479, filed Sep. 12, 2016, now U.S. Pat. No. 10,071,676, which is a continuation of U.S. patent application Ser. No. 14/164,682, filed Jan. 27, 2014, now U.S. Pat. No. 9,440,535, which is a continuation of U.S. patent application Ser. No. 13/887,727, filed May 6, 2013, now U.S. Pat. No. 8,636,393, which is a continuation of U.S. patent application Ser. No. 13/452,130, filed Apr. 20, 2012, now U.S. Pat. No. 8,434,919, which is a continuation of U.S. patent application Ser. No. 13/173,039, filed Jun. 30, 2011, now U.S. Pat. No. 8,162,518, which is a continuation of U.S. patent application Ser. No. 12/377,054, filed Feb. 10, 2009, now U.S. Pat. No. 7,972,045, which is a 371 of PCT Application No. PCT/US2007/075702, filed Aug. 10, 2007, which claims the benefit of U.S. provisional applications, Ser. No. 60/845,381, filed Sep. 18, 2006, and Ser. No. 60/837,408, filed Aug. 11, 2006, which are hereby incorporated herein by reference in their entireties.
Number | Name | Date | Kind |
---|---|---|---|
1472509 | Bitter | Oct 1923 | A |
2074251 | Braun | Mar 1937 | A |
2148119 | Grist | Feb 1939 | A |
2240843 | Gillespie | May 1941 | A |
2317400 | Paulus et al. | Apr 1943 | A |
2331144 | Sitter | Oct 1943 | A |
2339291 | Paulus et al. | Jan 1944 | A |
2424288 | Severy | Jul 1947 | A |
2598420 | Onksen, Jr. | May 1952 | A |
2632040 | Rabinow | Mar 1953 | A |
2750583 | McCullough | Jun 1956 | A |
2762932 | Falge et al. | Sep 1956 | A |
2827594 | Rabinow | Mar 1958 | A |
2855523 | Berger | Oct 1958 | A |
2856146 | Lehder | Oct 1958 | A |
2863064 | Rabinow | Dec 1958 | A |
2892094 | Lehovec | Jun 1959 | A |
2907920 | McIlvaine | Oct 1959 | A |
2912593 | Deuth | Nov 1959 | A |
2934676 | Miller et al. | Apr 1960 | A |
2959709 | Vanaman | Nov 1960 | A |
3008532 | Reed | Nov 1961 | A |
3011580 | Reid | Dec 1961 | A |
3069654 | Hough | Dec 1962 | A |
3085646 | Paifve | Apr 1963 | A |
3158835 | Hipkins | Nov 1964 | A |
3172496 | Rabinow | Mar 1965 | A |
3179845 | Kulwiec | Apr 1965 | A |
3201750 | Morin | Aug 1965 | A |
3208070 | Boicey | Sep 1965 | A |
3249761 | Baumanns | May 1966 | A |
3271577 | Miller et al. | Sep 1966 | A |
3325680 | Amacher | Jun 1967 | A |
3367616 | Bausch | Feb 1968 | A |
3411843 | Moller | Nov 1968 | A |
3486066 | Jones et al. | Dec 1969 | A |
3515472 | Schwitzgebel | Jun 1970 | A |
3572428 | Monaco | Mar 1971 | A |
3623671 | Hargroves | Nov 1971 | A |
3673560 | Barsh et al. | Jun 1972 | A |
3680951 | Jordan et al. | Aug 1972 | A |
3689695 | Rosenfield et al. | Sep 1972 | A |
3708668 | Tilley | Jan 1973 | A |
3751711 | Schick | Aug 1973 | A |
3845572 | McCanney | Nov 1974 | A |
3876940 | Wickord et al. | Apr 1975 | A |
3971065 | Bayer | Jul 1976 | A |
3985424 | Steinacher | Oct 1976 | A |
3986022 | Hyatt | Oct 1976 | A |
4003445 | De Bruine | Jan 1977 | A |
4037134 | Loper | Jul 1977 | A |
4044853 | Melke | Aug 1977 | A |
4049961 | Marcy | Sep 1977 | A |
4058796 | Oishi et al. | Nov 1977 | A |
4093364 | Miller | Jun 1978 | A |
4127778 | Leitz | Nov 1978 | A |
4139801 | Linares | Feb 1979 | A |
4143264 | Gilbert et al. | Mar 1979 | A |
4176728 | Otteblad et al. | Dec 1979 | A |
4200361 | Malvano et al. | Apr 1980 | A |
4209853 | Hyatt | Jun 1980 | A |
4214266 | Myers | Jul 1980 | A |
4218698 | Bart et al. | Aug 1980 | A |
4236099 | Rosenblum | Nov 1980 | A |
4238778 | Ohsumi | Dec 1980 | A |
4243196 | Toda et al. | Jan 1981 | A |
4247870 | Gabel et al. | Jan 1981 | A |
4249160 | Chilvers | Feb 1981 | A |
4254931 | Aikens et al. | Mar 1981 | A |
4257703 | Goodrich | Mar 1981 | A |
4266856 | Wainwright | May 1981 | A |
4277804 | Robison | Jul 1981 | A |
4278142 | Kono | Jul 1981 | A |
4281898 | Ochiai et al. | Aug 1981 | A |
4288814 | Talley et al. | Sep 1981 | A |
RE30835 | Giglia | Dec 1981 | E |
4348652 | Barnes et al. | Sep 1982 | A |
4348653 | Tsuzuki et al. | Sep 1982 | A |
4355271 | Noack | Oct 1982 | A |
4357558 | Massoni et al. | Nov 1982 | A |
4357594 | Ehrlich et al. | Nov 1982 | A |
4381888 | Momiyama | May 1983 | A |
4389537 | Tsunoda et al. | Jun 1983 | A |
4389639 | Torii et al. | Jun 1983 | A |
4390742 | Wideman | Jun 1983 | A |
4390895 | Sato et al. | Jun 1983 | A |
4401181 | Schwarz | Aug 1983 | A |
4403208 | Hodgson et al. | Sep 1983 | A |
4420238 | Felix | Dec 1983 | A |
4431896 | Lodetti | Feb 1984 | A |
4441125 | Parkinson | Apr 1984 | A |
4443057 | Bauer et al. | Apr 1984 | A |
4460831 | Oettinger et al. | Jul 1984 | A |
4464789 | Sternberg | Aug 1984 | A |
4471228 | Nishizawa et al. | Sep 1984 | A |
4481450 | Watanabe et al. | Nov 1984 | A |
4483011 | Brown | Nov 1984 | A |
4485402 | Searby | Nov 1984 | A |
4491390 | Tong-Shen | Jan 1985 | A |
4495589 | Hirzel | Jan 1985 | A |
4512637 | Ballmer | Apr 1985 | A |
4521804 | Bendell | Jun 1985 | A |
4529275 | Ballmer | Jul 1985 | A |
4532550 | Bendell et al. | Jul 1985 | A |
4538181 | Taylor | Aug 1985 | A |
4546551 | Franks | Oct 1985 | A |
4549208 | Kamejima et al. | Oct 1985 | A |
4564833 | Seko et al. | Jan 1986 | A |
4566032 | Hirooka et al. | Jan 1986 | A |
4571082 | Downs | Feb 1986 | A |
4572619 | Reininger et al. | Feb 1986 | A |
4580875 | Bechtel et al. | Apr 1986 | A |
4587522 | Warren | May 1986 | A |
4588041 | Tsuchihashi | May 1986 | A |
4599544 | Martin | Jul 1986 | A |
4600913 | Caine | Jul 1986 | A |
4601053 | Grumet | Jul 1986 | A |
4603946 | Kato et al. | Aug 1986 | A |
4614415 | Hyatt | Sep 1986 | A |
4620141 | McCumber et al. | Oct 1986 | A |
4623222 | Itoh et al. | Nov 1986 | A |
4625329 | Ishikawa et al. | Nov 1986 | A |
4626850 | Chey | Dec 1986 | A |
4629941 | Ellis et al. | Dec 1986 | A |
4630109 | Barton | Dec 1986 | A |
4632509 | Ohmi et al. | Dec 1986 | A |
4638287 | Umebayashi et al. | Jan 1987 | A |
4645320 | Muelling et al. | Feb 1987 | A |
4645975 | Meitzler et al. | Feb 1987 | A |
4647161 | Muller | Mar 1987 | A |
4647975 | Alston et al. | Mar 1987 | A |
4653316 | Fukuhara | Mar 1987 | A |
4665321 | Chang et al. | May 1987 | A |
4669825 | Itoh et al. | Jun 1987 | A |
4671614 | Catalano | Jun 1987 | A |
4671615 | Fukada et al. | Jun 1987 | A |
4672457 | Hyatt | Jun 1987 | A |
4676601 | Itoh et al. | Jun 1987 | A |
4679077 | Yuasa et al. | Jul 1987 | A |
4681431 | Sims et al. | Jul 1987 | A |
4688085 | Imaide | Aug 1987 | A |
4690508 | Jacob | Sep 1987 | A |
4692798 | Seko et al. | Sep 1987 | A |
4693788 | Berg et al. | Sep 1987 | A |
4697883 | Suzuki et al. | Oct 1987 | A |
4699484 | Howell et al. | Oct 1987 | A |
4701022 | Jacob | Oct 1987 | A |
4701613 | Watanabe et al. | Oct 1987 | A |
4713685 | Nishimura et al. | Dec 1987 | A |
4717830 | Botts | Jan 1988 | A |
4727290 | Smith et al. | Feb 1988 | A |
4728804 | Norsworthy | Mar 1988 | A |
4731669 | Hayashi et al. | Mar 1988 | A |
4731769 | Schaefer et al. | Mar 1988 | A |
4741603 | Miyagi et al. | May 1988 | A |
4755664 | Holmes et al. | Jul 1988 | A |
4758883 | Kawahara et al. | Jul 1988 | A |
4768135 | Kretschmer et al. | Aug 1988 | A |
4772942 | Tuck | Sep 1988 | A |
4779095 | Guerreri | Oct 1988 | A |
4785280 | Fubini et al. | Nov 1988 | A |
4789904 | Peterson | Dec 1988 | A |
4793690 | Gahan et al. | Dec 1988 | A |
4799267 | Kamejima et al. | Jan 1989 | A |
4805015 | Copeland | Feb 1989 | A |
4816828 | Feher | Mar 1989 | A |
4817948 | Simonelli | Apr 1989 | A |
4820933 | Hong et al. | Apr 1989 | A |
4825232 | Howdle | Apr 1989 | A |
4833469 | David | May 1989 | A |
4833534 | Paff et al. | May 1989 | A |
4838650 | Stewart et al. | Jun 1989 | A |
4839749 | Franklin | Jun 1989 | A |
4841348 | Shizukuishi et al. | Jun 1989 | A |
4843463 | Michetti | Jun 1989 | A |
4847489 | Dietrich | Jul 1989 | A |
4847772 | Michalopoulos et al. | Jul 1989 | A |
4849731 | Melocik | Jul 1989 | A |
4855822 | Narendra et al. | Aug 1989 | A |
4859031 | Berman et al. | Aug 1989 | A |
4862037 | Farber et al. | Aug 1989 | A |
4863130 | Marks, Jr. | Sep 1989 | A |
4867561 | Fujii et al. | Sep 1989 | A |
4870264 | Beha | Sep 1989 | A |
4871917 | O'Farrell et al. | Oct 1989 | A |
4872051 | Dye | Oct 1989 | A |
4881019 | Shiraishi et al. | Nov 1989 | A |
4882466 | Friel | Nov 1989 | A |
4882565 | Gallmeyer | Nov 1989 | A |
4883349 | Mittelhauser | Nov 1989 | A |
4884055 | Memmola | Nov 1989 | A |
4886960 | Molyneux et al. | Dec 1989 | A |
4891559 | Matsumoto et al. | Jan 1990 | A |
4892345 | Rachael, III | Jan 1990 | A |
4895790 | Swanson et al. | Jan 1990 | A |
4896030 | Miyaji | Jan 1990 | A |
4899296 | Khattak | Feb 1990 | A |
4900133 | Berman | Feb 1990 | A |
4905151 | Weiman et al. | Feb 1990 | A |
4906940 | Greene et al. | Mar 1990 | A |
4907870 | Brucker | Mar 1990 | A |
4910591 | Petrossian et al. | Mar 1990 | A |
4916374 | Schierbeek et al. | Apr 1990 | A |
4917477 | Bechtel et al. | Apr 1990 | A |
4926346 | Yokoyama | May 1990 | A |
4930742 | Schofield et al. | Jun 1990 | A |
4931937 | Kakinami et al. | Jun 1990 | A |
4936533 | Adams et al. | Jun 1990 | A |
4937796 | Tendler | Jun 1990 | A |
4948246 | Shigematsu | Aug 1990 | A |
4949186 | Peterson | Aug 1990 | A |
4953305 | Van Lente et al. | Sep 1990 | A |
4954962 | Evans, Jr. et al. | Sep 1990 | A |
4956591 | Schierbeek et al. | Sep 1990 | A |
4961625 | Wood et al. | Oct 1990 | A |
4963788 | King et al. | Oct 1990 | A |
4966441 | Conner | Oct 1990 | A |
4967319 | Seko | Oct 1990 | A |
4970509 | Kissinger, Sr. | Nov 1990 | A |
4970589 | Hanson et al. | Nov 1990 | A |
4970653 | Kenue | Nov 1990 | A |
4971405 | Hwang | Nov 1990 | A |
4971430 | Lynas | Nov 1990 | A |
4974078 | Tsai | Nov 1990 | A |
4975703 | Delisle et al. | Dec 1990 | A |
4985847 | Shioya et al. | Jan 1991 | A |
4987357 | Masaki | Jan 1991 | A |
4987410 | Berman et al. | Jan 1991 | A |
4991054 | Walters | Feb 1991 | A |
5001558 | Burley et al. | Mar 1991 | A |
5003288 | Wilhelm | Mar 1991 | A |
5003339 | Kikuchi et al. | Mar 1991 | A |
5008739 | D'Luna et al. | Apr 1991 | A |
5008946 | Ando | Apr 1991 | A |
5012082 | Watanabe | Apr 1991 | A |
5012092 | Kobayashi et al. | Apr 1991 | A |
5012335 | Cohodar | Apr 1991 | A |
5016977 | Baude et al. | May 1991 | A |
5020114 | Fujioka et al. | May 1991 | A |
5027001 | Torbert | Jun 1991 | A |
5027104 | Reid | Jun 1991 | A |
5027200 | Petrossian et al. | Jun 1991 | A |
5031101 | Kamimura et al. | Jul 1991 | A |
5036437 | Macks | Jul 1991 | A |
5044706 | Chen | Sep 1991 | A |
5044956 | Behensky et al. | Sep 1991 | A |
5050966 | Berman | Sep 1991 | A |
5051906 | Evans, Jr. et al. | Sep 1991 | A |
5055668 | French | Oct 1991 | A |
5059877 | Teder | Oct 1991 | A |
5059947 | Chen | Oct 1991 | A |
5063603 | Burt | Nov 1991 | A |
5064274 | Alten | Nov 1991 | A |
5072154 | Chen | Dec 1991 | A |
5075768 | Wirtz et al. | Dec 1991 | A |
5080207 | Horneffer | Jan 1992 | A |
5080309 | Ivins | Jan 1992 | A |
5081585 | Kurami et al. | Jan 1992 | A |
5086253 | Lawler | Feb 1992 | A |
5086510 | Guenther et al. | Feb 1992 | A |
5087969 | Kamada et al. | Feb 1992 | A |
5096287 | Kakinami et al. | Mar 1992 | A |
5097362 | Lynas | Mar 1992 | A |
5100093 | Rawlinson | Mar 1992 | A |
5101351 | Hattori | Mar 1992 | A |
5111289 | Lucas et al. | May 1992 | A |
5113721 | Polly | May 1992 | A |
5115398 | De Jong | May 1992 | A |
5121200 | Choi | Jun 1992 | A |
5122957 | Hattori | Jun 1992 | A |
5124549 | Michaels et al. | Jun 1992 | A |
5128769 | Arai et al. | Jul 1992 | A |
5130709 | Toyama et al. | Jul 1992 | A |
5133605 | Nakamura | Jul 1992 | A |
5137238 | Hutten | Aug 1992 | A |
5139327 | Tanaka | Aug 1992 | A |
5144685 | Nasar et al. | Sep 1992 | A |
5146340 | Dickerson et al. | Sep 1992 | A |
5148014 | Lynam et al. | Sep 1992 | A |
5153760 | Ahmed | Oct 1992 | A |
5155426 | Kurami | Oct 1992 | A |
5155775 | Brown | Oct 1992 | A |
5159557 | Ogawa | Oct 1992 | A |
5160780 | Ono et al. | Nov 1992 | A |
5160971 | Koshizawa | Nov 1992 | A |
5161632 | Asayama | Nov 1992 | A |
5162841 | Terashita | Nov 1992 | A |
5162861 | Tamburino et al. | Nov 1992 | A |
5163002 | Kurami | Nov 1992 | A |
5165108 | Asayama | Nov 1992 | A |
5166681 | Bottesch et al. | Nov 1992 | A |
5168355 | Asayama | Dec 1992 | A |
5168378 | Black | Dec 1992 | A |
5170374 | Shimohigashi et al. | Dec 1992 | A |
5172235 | Wilm et al. | Dec 1992 | A |
5172317 | Asanuma et al. | Dec 1992 | A |
5173881 | Sindle | Dec 1992 | A |
5177462 | Kajiwara | Jan 1993 | A |
5177606 | Koshizawa | Jan 1993 | A |
5177685 | Davis et al. | Jan 1993 | A |
5182502 | Slotkowski et al. | Jan 1993 | A |
5184956 | Langlais et al. | Feb 1993 | A |
5185812 | Yamashita et al. | Feb 1993 | A |
5187383 | Taccetta et al. | Feb 1993 | A |
5189561 | Hong | Feb 1993 | A |
5193000 | Lipton et al. | Mar 1993 | A |
5193029 | Schofield et al. | Mar 1993 | A |
5193894 | Lietar et al. | Mar 1993 | A |
5204536 | Vardi | Apr 1993 | A |
5204778 | Bechtel | Apr 1993 | A |
5208701 | Maeda | May 1993 | A |
5208750 | Kurami et al. | May 1993 | A |
5212468 | Adell | May 1993 | A |
5214408 | Asayama | May 1993 | A |
5216408 | Shirakawa | Jun 1993 | A |
5218414 | Kajiwara | Jun 1993 | A |
5220508 | Ninomiya et al. | Jun 1993 | A |
5223814 | Suman | Jun 1993 | A |
5223907 | Asayama | Jun 1993 | A |
5225827 | Persson | Jul 1993 | A |
5229941 | Hattori | Jul 1993 | A |
5230400 | Kakinami et al. | Jul 1993 | A |
5231379 | Wood et al. | Jul 1993 | A |
5233527 | Shinnosuke | Aug 1993 | A |
5234070 | Noah et al. | Aug 1993 | A |
5235178 | Hegyi | Aug 1993 | A |
5237249 | Levers | Aug 1993 | A |
5243524 | Ishida et al. | Sep 1993 | A |
5245422 | Borcherts et al. | Sep 1993 | A |
5246193 | Faidley | Sep 1993 | A |
5249126 | Hattori | Sep 1993 | A |
5249128 | Markandey et al. | Sep 1993 | A |
5249157 | Taylor | Sep 1993 | A |
5251680 | Minezawa et al. | Oct 1993 | A |
5253050 | Karasudani | Oct 1993 | A |
5253109 | O'Farrell et al. | Oct 1993 | A |
5265172 | Markandey et al. | Nov 1993 | A |
5266873 | Arditi et al. | Nov 1993 | A |
5267160 | Ito et al. | Nov 1993 | A |
5276389 | Levers | Jan 1994 | A |
5285060 | Larson et al. | Feb 1994 | A |
5289182 | Brillard et al. | Feb 1994 | A |
5289321 | Secor | Feb 1994 | A |
5291424 | Asayama et al. | Mar 1994 | A |
5293162 | Bachalo | Mar 1994 | A |
5298732 | Chen et al. | Mar 1994 | A |
5301115 | Nouso | Apr 1994 | A |
5302956 | Asbury et al. | Apr 1994 | A |
5304980 | Maekawa | Apr 1994 | A |
5305012 | Faris | Apr 1994 | A |
5307136 | Saneyoshi | Apr 1994 | A |
5307419 | Tsujino et al. | Apr 1994 | A |
5309137 | Kajiwara | May 1994 | A |
5313072 | Vachss | May 1994 | A |
5318143 | Parker et al. | Jun 1994 | A |
5321556 | Joe | Jun 1994 | A |
5325096 | Pakett | Jun 1994 | A |
5325386 | Jewell et al. | Jun 1994 | A |
5327288 | Wellington et al. | Jul 1994 | A |
5329206 | Slotkowski et al. | Jul 1994 | A |
5331312 | Kudoh | Jul 1994 | A |
5336980 | Levers | Aug 1994 | A |
5341437 | Nakayama | Aug 1994 | A |
5343206 | Ansaldi et al. | Aug 1994 | A |
5345266 | Denyer | Sep 1994 | A |
5347456 | Zhang et al. | Sep 1994 | A |
5351044 | Mathur et al. | Sep 1994 | A |
D351370 | Lawlor et al. | Oct 1994 | S |
5355118 | Fukuhara | Oct 1994 | A |
5359666 | Nakayama et al. | Oct 1994 | A |
5367457 | Ishida | Nov 1994 | A |
5369590 | Karasudani | Nov 1994 | A |
5371535 | Takizawa | Dec 1994 | A |
5373911 | Yasui | Dec 1994 | A |
5374852 | Parkes | Dec 1994 | A |
5379196 | Kobayashi et al. | Jan 1995 | A |
5379353 | Hasegawa et al. | Jan 1995 | A |
5381338 | Wysocki et al. | Jan 1995 | A |
5386285 | Asayama | Jan 1995 | A |
5388048 | Yavnayi et al. | Feb 1995 | A |
5394333 | Kao | Feb 1995 | A |
5398041 | Hyatt | Mar 1995 | A |
5406395 | Wilson et al. | Apr 1995 | A |
5406414 | O'Farrell et al. | Apr 1995 | A |
5408330 | Squicciarini et al. | Apr 1995 | A |
5408346 | Trissel et al. | Apr 1995 | A |
5410346 | Saneyoshi et al. | Apr 1995 | A |
5414257 | Stanton | May 1995 | A |
5414439 | Groves et al. | May 1995 | A |
5414461 | Kishi et al. | May 1995 | A |
5414625 | Hattori | May 1995 | A |
5416313 | Larson et al. | May 1995 | A |
5416318 | Hegyi | May 1995 | A |
5416478 | Morinaga | May 1995 | A |
5416711 | Gran et al. | May 1995 | A |
5424952 | Asayama | Jun 1995 | A |
5426294 | Kobayashi et al. | Jun 1995 | A |
5430431 | Nelson | Jul 1995 | A |
5430450 | Holmes | Jul 1995 | A |
5434407 | Bauer et al. | Jul 1995 | A |
5434927 | Brady et al. | Jul 1995 | A |
5436839 | Dausch et al. | Jul 1995 | A |
5440428 | Hegg et al. | Aug 1995 | A |
5444478 | Lelong et al. | Aug 1995 | A |
5448180 | Kienzler et al. | Sep 1995 | A |
5450057 | Watanabe | Sep 1995 | A |
5451822 | Bechtel et al. | Sep 1995 | A |
5457493 | Leddy et al. | Oct 1995 | A |
5459660 | Berra | Oct 1995 | A |
5461357 | Yoshioka et al. | Oct 1995 | A |
5461361 | Moore | Oct 1995 | A |
5465079 | Bouchard et al. | Nov 1995 | A |
5467284 | Yoshioka et al. | Nov 1995 | A |
5469298 | Suman et al. | Nov 1995 | A |
5471515 | Fossum et al. | Nov 1995 | A |
5473515 | Liu | Dec 1995 | A |
5475366 | Van Lente et al. | Dec 1995 | A |
5475494 | Nishida et al. | Dec 1995 | A |
5481257 | Brubaker et al. | Jan 1996 | A |
5482133 | Iwata et al. | Jan 1996 | A |
5483060 | Sugiura et al. | Jan 1996 | A |
5483168 | Reid | Jan 1996 | A |
5483453 | Uemura et al. | Jan 1996 | A |
5487116 | Nakano et al. | Jan 1996 | A |
5488496 | Pine | Jan 1996 | A |
5493269 | Durley et al. | Feb 1996 | A |
5493392 | Blackmon et al. | Feb 1996 | A |
5498866 | Bendicks et al. | Mar 1996 | A |
5500766 | Stonecypher | Mar 1996 | A |
5508592 | Lapatovich et al. | Apr 1996 | A |
5510983 | Lino | Apr 1996 | A |
5515448 | Nishitani | May 1996 | A |
5521633 | Nakajima et al. | May 1996 | A |
5528698 | Kamei et al. | Jun 1996 | A |
5529138 | Shaw et al. | Jun 1996 | A |
5530240 | Larson et al. | Jun 1996 | A |
5530330 | Baiden et al. | Jun 1996 | A |
5530420 | Tsuchiya et al. | Jun 1996 | A |
5530771 | Maekawa | Jun 1996 | A |
5535144 | Kise | Jul 1996 | A |
5535314 | Alves et al. | Jul 1996 | A |
5537003 | Bechtel et al. | Jul 1996 | A |
5539397 | Asanuma et al. | Jul 1996 | A |
5541590 | Nishio | Jul 1996 | A |
5545960 | Ishikawa | Aug 1996 | A |
5550677 | Schofield et al. | Aug 1996 | A |
5555136 | Waldmann et al. | Sep 1996 | A |
5555312 | Shima et al. | Sep 1996 | A |
5555503 | Kyrtsos et al. | Sep 1996 | A |
5555555 | Sato et al. | Sep 1996 | A |
5558123 | Castel et al. | Sep 1996 | A |
5559695 | Daily | Sep 1996 | A |
5562336 | Gotou | Oct 1996 | A |
5566224 | ul Azam et al. | Oct 1996 | A |
5568027 | Teder | Oct 1996 | A |
5568316 | Schrenk et al. | Oct 1996 | A |
5572315 | Krell | Nov 1996 | A |
5574443 | Hsieh | Nov 1996 | A |
5576687 | Blank et al. | Nov 1996 | A |
5581464 | Woll et al. | Dec 1996 | A |
5582383 | Mertens et al. | Dec 1996 | A |
5588123 | Loibl | Dec 1996 | A |
5594222 | Caldwell | Jan 1997 | A |
5596319 | Spry | Jan 1997 | A |
5596382 | Bamford | Jan 1997 | A |
5598164 | Reppas et al. | Jan 1997 | A |
5602457 | Anderson et al. | Feb 1997 | A |
5612686 | Takano et al. | Mar 1997 | A |
5612883 | Shaffer et al. | Mar 1997 | A |
5614788 | Mullins | Mar 1997 | A |
5614885 | Van Lente et al. | Mar 1997 | A |
5615857 | Hook | Apr 1997 | A |
5619370 | Guinosso | Apr 1997 | A |
5627586 | Yamasaki | May 1997 | A |
5633944 | Guibert et al. | May 1997 | A |
5634709 | Iwama | Jun 1997 | A |
5638116 | Shimoura et al. | Jun 1997 | A |
5642299 | Hardin et al. | Jun 1997 | A |
5646612 | Byon | Jul 1997 | A |
5648835 | Uzawa | Jul 1997 | A |
5650944 | Kise | Jul 1997 | A |
5660454 | Mori et al. | Aug 1997 | A |
5661303 | Teder | Aug 1997 | A |
5666028 | Bechtel et al. | Sep 1997 | A |
5667896 | Carter et al. | Sep 1997 | A |
5668663 | Varaprasad et al. | Sep 1997 | A |
5670935 | Schofield et al. | Sep 1997 | A |
5673019 | Dantoni | Sep 1997 | A |
5675489 | Pomerleau | Oct 1997 | A |
5676484 | Chamberlin et al. | Oct 1997 | A |
5677851 | Kingdon et al. | Oct 1997 | A |
5677979 | Squicciarini et al. | Oct 1997 | A |
5680263 | Zimmermann et al. | Oct 1997 | A |
D388107 | Huckins | Dec 1997 | S |
5699044 | Van Lente et al. | Dec 1997 | A |
5699057 | Ikeda et al. | Dec 1997 | A |
5699149 | Kuroda et al. | Dec 1997 | A |
5706355 | Raboisson et al. | Jan 1998 | A |
5707129 | Kobayashi | Jan 1998 | A |
5708410 | Blank et al. | Jan 1998 | A |
5710633 | Klappenbach et al. | Jan 1998 | A |
5715093 | Schierbeek et al. | Feb 1998 | A |
5719551 | Flick | Feb 1998 | A |
5724187 | Varaprasad et al. | Mar 1998 | A |
5724316 | Brunts | Mar 1998 | A |
5737226 | Olson et al. | Apr 1998 | A |
5757949 | Kinoshita et al. | May 1998 | A |
5760826 | Nayar | Jun 1998 | A |
5760828 | Cortes | Jun 1998 | A |
5760931 | Saburi et al. | Jun 1998 | A |
5760962 | Schofield et al. | Jun 1998 | A |
5761094 | Olson et al. | Jun 1998 | A |
5764139 | Nojima et al. | Jun 1998 | A |
5765116 | Wilson-Jones et al. | Jun 1998 | A |
5765940 | Levy et al. | Jun 1998 | A |
5781105 | Bitar et al. | Jul 1998 | A |
5781437 | Wiemer et al. | Jul 1998 | A |
5786772 | Schofield et al. | Jul 1998 | A |
5790403 | Nakayama | Aug 1998 | A |
5790973 | Blaker et al. | Aug 1998 | A |
5793308 | Rosinski et al. | Aug 1998 | A |
5793420 | Schmidt | Aug 1998 | A |
5796094 | Schofield et al. | Aug 1998 | A |
5798575 | O'Farrell et al. | Aug 1998 | A |
5804719 | Didelot et al. | Sep 1998 | A |
5808589 | Fergason | Sep 1998 | A |
5811888 | Hsieh | Sep 1998 | A |
5820097 | Spooner | Oct 1998 | A |
5835255 | Miles | Nov 1998 | A |
5835613 | Breed et al. | Nov 1998 | A |
5835614 | Aoyama et al. | Nov 1998 | A |
5837994 | Stam et al. | Nov 1998 | A |
5841126 | Fossum et al. | Nov 1998 | A |
5844505 | Van Ryzin | Dec 1998 | A |
5844682 | Kiyomoto et al. | Dec 1998 | A |
5845000 | Breed et al. | Dec 1998 | A |
5847755 | Wixson et al. | Dec 1998 | A |
5848802 | Breed et al. | Dec 1998 | A |
5850176 | Kinoshita et al. | Dec 1998 | A |
5850254 | Takano et al. | Dec 1998 | A |
5867591 | Onda | Feb 1999 | A |
5877707 | Kowalick | Mar 1999 | A |
5877897 | Schofield et al. | Mar 1999 | A |
5878370 | Olson | Mar 1999 | A |
5883193 | Karim | Mar 1999 | A |
5883684 | Millikan et al. | Mar 1999 | A |
5883739 | Ashihara et al. | Mar 1999 | A |
5884212 | Lion | Mar 1999 | A |
5890021 | Onoda | Mar 1999 | A |
5890083 | Franke et al. | Mar 1999 | A |
5896085 | Mori et al. | Apr 1999 | A |
5899956 | Chan | May 1999 | A |
5904725 | Iisaka et al. | May 1999 | A |
5905457 | Rashid | May 1999 | A |
5912534 | Benedict | Jun 1999 | A |
5914815 | Bos | Jun 1999 | A |
5920367 | Kajimoto et al. | Jul 1999 | A |
5922036 | Yasui et al. | Jul 1999 | A |
5923027 | Stam et al. | Jul 1999 | A |
5929784 | Kawaziri et al. | Jul 1999 | A |
5929786 | Schofield et al. | Jul 1999 | A |
5938320 | Crandall | Aug 1999 | A |
5938810 | De Vries, Jr et al. | Aug 1999 | A |
5940120 | Frankhouse et al. | Aug 1999 | A |
5942853 | Piscart | Aug 1999 | A |
5949331 | Schofield et al. | Sep 1999 | A |
5955941 | Pruksch et al. | Sep 1999 | A |
5956181 | Lin | Sep 1999 | A |
5959367 | O'Farrell et al. | Sep 1999 | A |
5959555 | Furuta | Sep 1999 | A |
5961571 | Gorr et al. | Oct 1999 | A |
5963247 | Banitt | Oct 1999 | A |
5964822 | Alland et al. | Oct 1999 | A |
5971552 | O'Farrell et al. | Oct 1999 | A |
5982288 | Sawatari et al. | Nov 1999 | A |
5986796 | Miles | Nov 1999 | A |
5990469 | Bechtel et al. | Nov 1999 | A |
5990649 | Nagao et al. | Nov 1999 | A |
5991427 | Kakinami et al. | Nov 1999 | A |
6001486 | Varaprasad et al. | Dec 1999 | A |
6009336 | Harris et al. | Dec 1999 | A |
6020704 | Buschur | Feb 2000 | A |
6028537 | Suman et al. | Feb 2000 | A |
6031484 | Bullinger et al. | Feb 2000 | A |
6037860 | Zander et al. | Mar 2000 | A |
6037975 | Aoyama | Mar 2000 | A |
6049171 | Stam et al. | Apr 2000 | A |
6052124 | Stein et al. | Apr 2000 | A |
6057754 | Kinoshita et al. | May 2000 | A |
6066933 | Ponziana | May 2000 | A |
6084519 | Coulling et al. | Jul 2000 | A |
6087953 | DeLine et al. | Jul 2000 | A |
6091833 | Yasui et al. | Jul 2000 | A |
6094198 | Shashua | Jul 2000 | A |
6097023 | Schofield et al. | Aug 2000 | A |
6097024 | Stam et al. | Aug 2000 | A |
6100811 | Hsu et al. | Aug 2000 | A |
6107939 | Sorden | Aug 2000 | A |
6116743 | Hoek | Sep 2000 | A |
6122597 | Saneyoshi et al. | Sep 2000 | A |
6124647 | Marcus et al. | Sep 2000 | A |
6124886 | DeLine et al. | Sep 2000 | A |
6139172 | Bos et al. | Oct 2000 | A |
6140980 | Spitzer et al. | Oct 2000 | A |
6144022 | Tenenbaum et al. | Nov 2000 | A |
6144158 | Beam | Nov 2000 | A |
6150014 | Chu et al. | Nov 2000 | A |
6150930 | Cooper | Nov 2000 | A |
6151065 | Steed et al. | Nov 2000 | A |
6151539 | Bergholz et al. | Nov 2000 | A |
6158655 | DeVries, Jr. et al. | Dec 2000 | A |
6166628 | Andreas | Dec 2000 | A |
6170955 | Campbell et al. | Jan 2001 | B1 |
6172613 | DeLine et al. | Jan 2001 | B1 |
6175164 | O'Farrell et al. | Jan 2001 | B1 |
6175300 | Kendrick | Jan 2001 | B1 |
6176590 | Prevost et al. | Jan 2001 | B1 |
6188939 | Morgan et al. | Feb 2001 | B1 |
6198409 | Schofield et al. | Mar 2001 | B1 |
6201642 | Bos | Mar 2001 | B1 |
6211907 | Scaman et al. | Apr 2001 | B1 |
6218934 | Regan | Apr 2001 | B1 |
6219444 | Shashua et al. | Apr 2001 | B1 |
6222447 | Schofield et al. | Apr 2001 | B1 |
6222460 | DeLine et al. | Apr 2001 | B1 |
6226061 | Tagusa | May 2001 | B1 |
6229319 | Johnson | May 2001 | B1 |
6243003 | DeLine et al. | Jun 2001 | B1 |
6247819 | Turnbull et al. | Jun 2001 | B1 |
6250148 | Lynam | Jun 2001 | B1 |
6259412 | Duroux | Jul 2001 | B1 |
6259423 | Tokito et al. | Jul 2001 | B1 |
6266082 | Yonezawa et al. | Jul 2001 | B1 |
6266442 | Laumeyer et al. | Jul 2001 | B1 |
6278377 | DeLine et al. | Aug 2001 | B1 |
6281804 | Haller et al. | Aug 2001 | B1 |
6285393 | Shimoura et al. | Sep 2001 | B1 |
6285778 | Nakajima et al. | Sep 2001 | B1 |
6291905 | Drummond et al. | Sep 2001 | B1 |
6291906 | Marcus et al. | Sep 2001 | B1 |
6292752 | Franke et al. | Sep 2001 | B1 |
6294989 | Schofield et al. | Sep 2001 | B1 |
6297781 | Turnbull et al. | Oct 2001 | B1 |
6302545 | Schofield et al. | Oct 2001 | B1 |
6310611 | Caldwell | Oct 2001 | B1 |
6311119 | Sawamoto et al. | Oct 2001 | B2 |
6313454 | Bos et al. | Nov 2001 | B1 |
6315421 | Apfelbeck et al. | Nov 2001 | B1 |
6317057 | Lee | Nov 2001 | B1 |
6318870 | Spooner et al. | Nov 2001 | B1 |
6320176 | Schofield et al. | Nov 2001 | B1 |
6320282 | Caldwell | Nov 2001 | B1 |
6324450 | Iwama | Nov 2001 | B1 |
6326613 | Heslin et al. | Dec 2001 | B1 |
6329925 | Skiver et al. | Dec 2001 | B1 |
6333759 | Mazzilli | Dec 2001 | B1 |
6341523 | Lynam | Jan 2002 | B2 |
6353392 | Schofield et al. | Mar 2002 | B1 |
6359392 | He | Mar 2002 | B1 |
6362729 | Hellmann et al. | Mar 2002 | B1 |
6366213 | DeLine et al. | Apr 2002 | B2 |
6366236 | Farmer et al. | Apr 2002 | B1 |
6370329 | Teuchert | Apr 2002 | B1 |
6388565 | Bernhard et al. | May 2002 | B1 |
6388580 | Graham | May 2002 | B1 |
6389340 | Rayner | May 2002 | B1 |
6392218 | Kuehnle | May 2002 | B1 |
6396397 | Bos et al. | May 2002 | B1 |
6396408 | Drummond et al. | May 2002 | B2 |
6411204 | Bloomfield et al. | Jun 2002 | B1 |
6411328 | Franke et al. | Jun 2002 | B1 |
6420975 | DeLine et al. | Jul 2002 | B1 |
6424273 | Gutta et al. | Jul 2002 | B1 |
6428172 | Hutzel et al. | Aug 2002 | B1 |
6429594 | Stam et al. | Aug 2002 | B1 |
6430303 | Naoi et al. | Aug 2002 | B1 |
6433676 | DeLine et al. | Aug 2002 | B2 |
6433817 | Guerra | Aug 2002 | B1 |
6441748 | Takagi et al. | Aug 2002 | B1 |
6442465 | Breed et al. | Aug 2002 | B2 |
6445287 | Schofield et al. | Sep 2002 | B1 |
6445809 | Sasaki et al. | Sep 2002 | B1 |
6449540 | Rayner | Sep 2002 | B1 |
6452148 | Bendicks et al. | Sep 2002 | B1 |
6466136 | DeLine et al. | Oct 2002 | B2 |
6466684 | Sasaki et al. | Oct 2002 | B1 |
6469739 | Bechtel et al. | Oct 2002 | B1 |
6472977 | Pochmuller | Oct 2002 | B1 |
6472979 | Schofield et al. | Oct 2002 | B2 |
6477260 | Shimomura | Nov 2002 | B1 |
6477464 | McCarthy et al. | Nov 2002 | B2 |
6483438 | DeLine et al. | Nov 2002 | B2 |
6485155 | Duroux et al. | Nov 2002 | B1 |
6497503 | Dassanayake et al. | Dec 2002 | B1 |
6498620 | Schofield et al. | Dec 2002 | B2 |
6509832 | Bauer et al. | Jan 2003 | B1 |
6513252 | Schierbeek et al. | Feb 2003 | B1 |
6515378 | Drummond et al. | Feb 2003 | B2 |
6516272 | Lin | Feb 2003 | B2 |
6516664 | Lynam | Feb 2003 | B2 |
6523964 | Schofield et al. | Feb 2003 | B2 |
6534884 | Marcus et al. | Mar 2003 | B2 |
6535242 | Strumolo et al. | Mar 2003 | B1 |
6539306 | Turnbull | Mar 2003 | B2 |
6540193 | DeLine | Apr 2003 | B1 |
6547133 | Devries, Jr. et al. | Apr 2003 | B1 |
6553130 | Lemelson et al. | Apr 2003 | B1 |
6559435 | Schofield et al. | May 2003 | B2 |
6570998 | Ohtsuka et al. | May 2003 | B1 |
6574033 | Chui et al. | Jun 2003 | B1 |
6577334 | Kawai et al. | Jun 2003 | B1 |
6578017 | Ebersole et al. | Jun 2003 | B1 |
6587573 | Stam et al. | Jul 2003 | B1 |
6587968 | Leyva | Jul 2003 | B1 |
6589625 | Kothari et al. | Jul 2003 | B1 |
6593011 | Liu et al. | Jul 2003 | B2 |
6593565 | Heslin et al. | Jul 2003 | B2 |
6593698 | Stam et al. | Jul 2003 | B2 |
6593960 | Sugimoto et al. | Jul 2003 | B1 |
6594583 | Ogura et al. | Jul 2003 | B2 |
6611202 | Schofield et al. | Aug 2003 | B2 |
6611610 | Stam et al. | Aug 2003 | B1 |
6614579 | Roberts et al. | Sep 2003 | B2 |
6617564 | Ockerse et al. | Sep 2003 | B2 |
6627918 | Getz et al. | Sep 2003 | B2 |
6631316 | Stam et al. | Oct 2003 | B2 |
6631994 | Suzuki et al. | Oct 2003 | B2 |
6636258 | Strumolo | Oct 2003 | B2 |
6648477 | Hutzel et al. | Nov 2003 | B2 |
6650233 | DeLine et al. | Nov 2003 | B2 |
6650455 | Miles | Nov 2003 | B2 |
6653614 | Stam et al. | Nov 2003 | B2 |
6672731 | Schnell et al. | Jan 2004 | B2 |
6674562 | Miles | Jan 2004 | B1 |
6674878 | Retterath et al. | Jan 2004 | B2 |
6678056 | Downs | Jan 2004 | B2 |
6678590 | Burchfiel | Jan 2004 | B1 |
6678614 | McCarthy et al. | Jan 2004 | B2 |
6680792 | Miles | Jan 2004 | B2 |
6681163 | Stam et al. | Jan 2004 | B2 |
6690268 | Schofield et al. | Feb 2004 | B2 |
6700605 | Toyoda et al. | Mar 2004 | B1 |
6703925 | Steffel | Mar 2004 | B2 |
6704621 | Stein et al. | Mar 2004 | B1 |
6710908 | Miles et al. | Mar 2004 | B2 |
6711474 | Treyz et al. | Mar 2004 | B1 |
6714331 | Lewis et al. | Mar 2004 | B2 |
6717524 | DeLine et al. | Apr 2004 | B2 |
6717610 | Bos et al. | Apr 2004 | B1 |
6728393 | Stam et al. | Apr 2004 | B2 |
6728623 | Takenaga et al. | Apr 2004 | B2 |
6735506 | Breed et al. | May 2004 | B2 |
6738088 | Uskolovsky et al. | May 2004 | B1 |
6741186 | Ross | May 2004 | B2 |
6741377 | Miles | May 2004 | B2 |
6744353 | Sjonell | Jun 2004 | B2 |
6754367 | Ito et al. | Jun 2004 | B1 |
6757109 | Bos | Jun 2004 | B2 |
6762867 | Lippert et al. | Jul 2004 | B2 |
6764210 | Akiyama | Jul 2004 | B2 |
6765480 | Tseng | Jul 2004 | B2 |
6774988 | Stam et al. | Aug 2004 | B2 |
6784828 | Delcheccolo et al. | Aug 2004 | B2 |
6794119 | Miles | Sep 2004 | B2 |
6795221 | Urey | Sep 2004 | B1 |
6801127 | Mizusawa et al. | Oct 2004 | B2 |
6801244 | Takeda et al. | Oct 2004 | B2 |
6802617 | Schofield et al. | Oct 2004 | B2 |
6806452 | Bos et al. | Oct 2004 | B2 |
6807287 | Hermans | Oct 2004 | B1 |
6811330 | Tozawa | Nov 2004 | B1 |
6812463 | Okada | Nov 2004 | B2 |
6813545 | Stromme | Nov 2004 | B2 |
6819231 | Berberich et al. | Nov 2004 | B2 |
6819779 | Nichani | Nov 2004 | B1 |
6822563 | Bos et al. | Nov 2004 | B2 |
6823241 | Shirato et al. | Nov 2004 | B2 |
6823261 | Sekiguchi | Nov 2004 | B2 |
6824281 | Schofield et al. | Nov 2004 | B2 |
6831261 | Schofield et al. | Dec 2004 | B2 |
6838980 | Gloger et al. | Jan 2005 | B2 |
6842189 | Park | Jan 2005 | B2 |
6847487 | Burgner | Jan 2005 | B2 |
6850629 | Jeon | Feb 2005 | B2 |
6853738 | Nishigaki et al. | Feb 2005 | B1 |
6859148 | Miller et al. | Feb 2005 | B2 |
6861809 | Stam | Mar 2005 | B2 |
6864930 | Matsushita et al. | Mar 2005 | B2 |
6873253 | Veziris | Mar 2005 | B2 |
6882287 | Schofield | Apr 2005 | B2 |
6888447 | Hori et al. | May 2005 | B2 |
6889161 | Winner et al. | May 2005 | B2 |
6891563 | Schofield et al. | May 2005 | B2 |
6898518 | Padmanabhan | May 2005 | B2 |
6906620 | Nakai et al. | Jun 2005 | B2 |
6906639 | Lemelson et al. | Jun 2005 | B2 |
6909753 | Meehan et al. | Jun 2005 | B2 |
6914521 | Rothkop | Jul 2005 | B2 |
6928180 | Stam et al. | Aug 2005 | B2 |
6932669 | Lee et al. | Aug 2005 | B2 |
6933837 | Gunderson et al. | Aug 2005 | B2 |
6940423 | Takagi et al. | Sep 2005 | B2 |
6946978 | Schofield | Sep 2005 | B2 |
6950035 | Tanaka et al. | Sep 2005 | B2 |
6953253 | Schofield et al. | Oct 2005 | B2 |
6956469 | Hirvonen et al. | Oct 2005 | B2 |
6959994 | Fujikawa et al. | Nov 2005 | B2 |
6961178 | Sugino et al. | Nov 2005 | B2 |
6961661 | Sekiguchi | Nov 2005 | B2 |
6963661 | Hattori et al. | Nov 2005 | B1 |
6967569 | Weber et al. | Nov 2005 | B2 |
6968736 | Lynam | Nov 2005 | B2 |
6975775 | Rykowski et al. | Dec 2005 | B2 |
6980092 | Turnbull et al. | Dec 2005 | B2 |
6989736 | Berberich et al. | Jan 2006 | B2 |
6990397 | Albou et al. | Jan 2006 | B2 |
6995687 | Lang et al. | Feb 2006 | B2 |
7004593 | Weller et al. | Feb 2006 | B2 |
7004606 | Schofield | Feb 2006 | B2 |
7005974 | McMahon et al. | Feb 2006 | B2 |
7012507 | DeLine et al. | Mar 2006 | B2 |
7012727 | Hutzel et al. | Mar 2006 | B2 |
7023331 | Kodama | Apr 2006 | B2 |
7027387 | Reinold et al. | Apr 2006 | B2 |
7027615 | Chen | Apr 2006 | B2 |
7030738 | Ishii | Apr 2006 | B2 |
7030775 | Sekiguchi | Apr 2006 | B2 |
7030778 | Ra | Apr 2006 | B2 |
7038577 | Pawlicki et al. | May 2006 | B2 |
7046448 | Burgner | May 2006 | B2 |
7057505 | Iwamoto | Jun 2006 | B2 |
7057681 | Hinata et al. | Jun 2006 | B2 |
7062300 | Kim | Jun 2006 | B1 |
7065432 | Moisel et al. | Jun 2006 | B2 |
7068289 | Satoh et al. | Jun 2006 | B2 |
7068844 | Javidi et al. | Jun 2006 | B1 |
7085633 | Nishira et al. | Aug 2006 | B2 |
7085637 | Breed et al. | Aug 2006 | B2 |
7091837 | Nakai et al. | Aug 2006 | B2 |
7092548 | Laumeyer et al. | Aug 2006 | B2 |
7095432 | Nakayama et al. | Aug 2006 | B2 |
7106213 | White | Sep 2006 | B2 |
7110021 | Nobori et al. | Sep 2006 | B2 |
7110156 | Lawlor et al. | Sep 2006 | B2 |
7113867 | Stein | Sep 2006 | B1 |
7116246 | Winter et al. | Oct 2006 | B2 |
7121028 | Shoen et al. | Oct 2006 | B2 |
7123168 | Schofield | Oct 2006 | B2 |
7133661 | Hatae et al. | Nov 2006 | B2 |
7149613 | Stam et al. | Dec 2006 | B2 |
7151996 | Stein | Dec 2006 | B2 |
7167796 | Taylor et al. | Jan 2007 | B2 |
7171027 | Satoh | Jan 2007 | B2 |
7184585 | Hamza et al. | Feb 2007 | B2 |
7187498 | Bengoechea et al. | Mar 2007 | B2 |
7188963 | Schofield et al. | Mar 2007 | B2 |
7195381 | Lynam et al. | Mar 2007 | B2 |
7202776 | Breed | Apr 2007 | B2 |
7202987 | Varaprasad et al. | Apr 2007 | B2 |
7205904 | Schofield | Apr 2007 | B2 |
7221363 | Roberts et al. | May 2007 | B2 |
7224324 | Quist et al. | May 2007 | B2 |
7227459 | Bos et al. | Jun 2007 | B2 |
7227611 | Hull et al. | Jun 2007 | B2 |
7235918 | McCullough et al. | Jun 2007 | B2 |
7248283 | Takagi et al. | Jul 2007 | B2 |
7248344 | Morcom | Jul 2007 | B2 |
7249860 | Kulas et al. | Jul 2007 | B2 |
7253723 | Lindahl et al. | Aug 2007 | B2 |
7255451 | McCabe et al. | Aug 2007 | B2 |
7271951 | Weber et al. | Sep 2007 | B2 |
7304661 | Ishikura | Dec 2007 | B2 |
7311406 | Schofield et al. | Dec 2007 | B2 |
7325934 | Schofield et al. | Feb 2008 | B2 |
7325935 | Schofield et al. | Feb 2008 | B2 |
7337055 | Matsumoto et al. | Feb 2008 | B2 |
7338177 | Lynam | Mar 2008 | B2 |
7339149 | Schofield et al. | Mar 2008 | B1 |
7344261 | Schofield et al. | Mar 2008 | B2 |
7355524 | Schofield | Apr 2008 | B2 |
7360932 | Uken et al. | Apr 2008 | B2 |
7362883 | Otsuka et al. | Apr 2008 | B2 |
7370983 | DeWind et al. | May 2008 | B2 |
7375803 | Bamji | May 2008 | B1 |
7380948 | Schofield et al. | Jun 2008 | B2 |
7388182 | Schofield et al. | Jun 2008 | B2 |
7402786 | Schofield et al. | Jul 2008 | B2 |
7403659 | Das et al. | Jul 2008 | B2 |
7420756 | Lynam | Sep 2008 | B2 |
7423248 | Schofield et al. | Sep 2008 | B2 |
7423821 | Bechtel et al. | Sep 2008 | B2 |
7425076 | Schofield et al. | Sep 2008 | B2 |
7429998 | Kawauchi et al. | Sep 2008 | B2 |
7432248 | Roberts et al. | Oct 2008 | B2 |
7432967 | Bechtel et al. | Oct 2008 | B2 |
7446924 | Schofield et al. | Nov 2008 | B2 |
7459664 | Schofield et al. | Dec 2008 | B2 |
7460007 | Schofield et al. | Dec 2008 | B2 |
7463138 | Pawlicki et al. | Dec 2008 | B2 |
7468652 | DeLine et al. | Dec 2008 | B2 |
7474963 | Taylor et al. | Jan 2009 | B2 |
7480149 | DeWard et al. | Jan 2009 | B2 |
7489374 | Utsumi et al. | Feb 2009 | B2 |
7495719 | Adachi et al. | Feb 2009 | B2 |
7525604 | Xue | Apr 2009 | B2 |
7526103 | Schofield et al. | Apr 2009 | B2 |
7533998 | Schofield et al. | May 2009 | B2 |
7541743 | Salmeen et al. | Jun 2009 | B2 |
7543946 | Ockerse et al. | Jun 2009 | B2 |
7545429 | Travis | Jun 2009 | B2 |
7548291 | Lee et al. | Jun 2009 | B2 |
7551103 | Schofield | Jun 2009 | B2 |
7561181 | Schofield et al. | Jul 2009 | B2 |
7565006 | Stam et al. | Jul 2009 | B2 |
7566639 | Kohda | Jul 2009 | B2 |
7566851 | Stein et al. | Jul 2009 | B2 |
7567291 | Bechtel et al. | Jul 2009 | B2 |
7605856 | Imoto | Oct 2009 | B2 |
7613327 | Stam et al. | Nov 2009 | B2 |
7616781 | Schofield et al. | Nov 2009 | B2 |
7619508 | Lynam et al. | Nov 2009 | B2 |
7629996 | Rademacher et al. | Dec 2009 | B2 |
7633383 | Dunsmoir et al. | Dec 2009 | B2 |
7639149 | Katoh | Dec 2009 | B2 |
7650030 | Shan et al. | Jan 2010 | B2 |
7653215 | Stam | Jan 2010 | B2 |
7655894 | Schofield et al. | Feb 2010 | B2 |
7663798 | Tonar et al. | Feb 2010 | B2 |
7676087 | Dhua et al. | Mar 2010 | B2 |
7679498 | Pawlicki et al. | Mar 2010 | B2 |
7683326 | Stam et al. | Mar 2010 | B2 |
7702133 | Muramatsu et al. | Apr 2010 | B2 |
7719408 | DeWard et al. | May 2010 | B2 |
7720580 | Higgins-Luthman | May 2010 | B2 |
7724434 | Cross et al. | May 2010 | B2 |
7731403 | Lynam et al. | Jun 2010 | B2 |
7742864 | Sekiguchi | Jun 2010 | B2 |
7786898 | Stein et al. | Aug 2010 | B2 |
7791694 | Molsen et al. | Sep 2010 | B2 |
7792329 | Schofield et al. | Sep 2010 | B2 |
7825600 | Stam et al. | Nov 2010 | B2 |
7842154 | Lynam | Nov 2010 | B2 |
7843451 | Lafon | Nov 2010 | B2 |
7854514 | Conner et al. | Dec 2010 | B2 |
7855755 | Weller et al. | Dec 2010 | B2 |
7855778 | Yung et al. | Dec 2010 | B2 |
7859565 | Schofield et al. | Dec 2010 | B2 |
7873187 | Schofield et al. | Jan 2011 | B2 |
7877175 | Higgins-Luthman | Jan 2011 | B2 |
7881496 | Camilleri et al. | Feb 2011 | B2 |
7903324 | Kobayashi et al. | Mar 2011 | B2 |
7903335 | Nieuwkerk et al. | Mar 2011 | B2 |
7914187 | Higgins-Luthman et al. | Mar 2011 | B2 |
7914188 | DeLine et al. | Mar 2011 | B2 |
7930160 | Hosagrahara et al. | Apr 2011 | B1 |
7949152 | Schofield et al. | May 2011 | B2 |
7965357 | Van De Witte et al. | Jun 2011 | B2 |
7972045 | Schofield | Jul 2011 | B2 |
7991522 | Higgins-Luthman | Aug 2011 | B2 |
7994462 | Schofield et al. | Aug 2011 | B2 |
7995067 | Navon | Aug 2011 | B2 |
8004392 | DeLine et al. | Aug 2011 | B2 |
8017898 | Lu et al. | Sep 2011 | B2 |
8027691 | Bernas et al. | Sep 2011 | B2 |
8045760 | Stam et al. | Oct 2011 | B2 |
8063759 | Bos et al. | Nov 2011 | B2 |
8064643 | Stein et al. | Nov 2011 | B2 |
8082101 | Stein et al. | Dec 2011 | B2 |
8090153 | Schofield et al. | Jan 2012 | B2 |
8094002 | Schofield et al. | Jan 2012 | B2 |
8095310 | Taylor et al. | Jan 2012 | B2 |
8098142 | Schofield et al. | Jan 2012 | B2 |
8100568 | DeLine et al. | Jan 2012 | B2 |
8116929 | Higgins-Luthman | Feb 2012 | B2 |
8120652 | Bechtel et al. | Feb 2012 | B2 |
8162518 | Schofield | Apr 2012 | B2 |
8164628 | Stein et al. | Apr 2012 | B2 |
8179437 | Schofield et al. | May 2012 | B2 |
8184159 | Luo | May 2012 | B2 |
8203440 | Schofield et al. | Jun 2012 | B2 |
8203443 | Bos et al. | Jun 2012 | B2 |
8222588 | Schofield et al. | Jul 2012 | B2 |
8224031 | Saito | Jul 2012 | B2 |
8233045 | Luo et al. | Jul 2012 | B2 |
8254635 | Stein et al. | Aug 2012 | B2 |
8288711 | Heslin et al. | Oct 2012 | B2 |
8289142 | Pawlicki et al. | Oct 2012 | B2 |
8289430 | Bechtel et al. | Oct 2012 | B2 |
8300058 | Navon et al. | Oct 2012 | B2 |
8305471 | Bechtel et al. | Nov 2012 | B2 |
8308325 | Takayanagi et al. | Nov 2012 | B2 |
8314689 | Schofield et al. | Nov 2012 | B2 |
8324552 | Schofield et al. | Dec 2012 | B2 |
8325028 | Schofield et al. | Dec 2012 | B2 |
8325986 | Schofield et al. | Dec 2012 | B2 |
8339526 | Minikey, Jr. et al. | Dec 2012 | B2 |
8350683 | DeLine et al. | Jan 2013 | B2 |
8362883 | Hale et al. | Jan 2013 | B2 |
8378851 | Stein et al. | Feb 2013 | B2 |
8386114 | Higgins-Luthman | Feb 2013 | B2 |
8405726 | Schofield et al. | Mar 2013 | B2 |
8414137 | Quinn et al. | Apr 2013 | B2 |
8434919 | Schofield | May 2013 | B2 |
8452055 | Stein et al. | May 2013 | B2 |
8481910 | Schofield et al. | Jul 2013 | B2 |
8481916 | Heslin et al. | Jul 2013 | B2 |
8492698 | Schofield et al. | Jul 2013 | B2 |
8508593 | Schofield et al. | Aug 2013 | B1 |
8513590 | Heslin et al. | Aug 2013 | B2 |
8531278 | DeWard et al. | Sep 2013 | B2 |
8531279 | DeLine et al. | Sep 2013 | B2 |
8534887 | DeLine et al. | Sep 2013 | B2 |
8538205 | Sixsou et al. | Sep 2013 | B2 |
8543330 | Taylor et al. | Sep 2013 | B2 |
8553088 | Stein et al. | Oct 2013 | B2 |
8593521 | Schofield et al. | Nov 2013 | B2 |
8599001 | Schofield et al. | Dec 2013 | B2 |
8629768 | Bos et al. | Jan 2014 | B2 |
8636393 | Schofield | Jan 2014 | B2 |
8637801 | Schofield et al. | Jan 2014 | B2 |
8643724 | Schofield et al. | Feb 2014 | B2 |
8656221 | Sixsou et al. | Feb 2014 | B2 |
8665079 | Pawlicki et al. | Mar 2014 | B2 |
8676491 | Taylor et al. | Mar 2014 | B2 |
8686840 | Drummond et al. | Apr 2014 | B2 |
8692659 | Schofield et al. | Apr 2014 | B2 |
8818042 | Schofield et al. | Aug 2014 | B2 |
9008369 | Schofield et al. | Apr 2015 | B2 |
9018577 | Lu et al. | Apr 2015 | B2 |
9171217 | Pawlicki et al. | Oct 2015 | B2 |
9191634 | Schofield et al. | Nov 2015 | B2 |
9428192 | Schofield et al. | Aug 2016 | B2 |
9440535 | Schofield | Sep 2016 | B2 |
10071676 | Schofield | Sep 2018 | B2 |
10787116 | Schofield | Sep 2020 | B2 |
11148583 | Schofield | Oct 2021 | B2 |
11396257 | Schofield | Jul 2022 | B2 |
11623559 | Schofield | Apr 2023 | B2 |
20010002451 | Breed | May 2001 | A1 |
20020003571 | Schofield et al. | Jan 2002 | A1 |
20020005778 | Breed et al. | Jan 2002 | A1 |
20020011611 | Huang et al. | Jan 2002 | A1 |
20020029103 | Breed et al. | Mar 2002 | A1 |
20020060522 | Stam et al. | May 2002 | A1 |
20020080235 | Jeon | Jun 2002 | A1 |
20020113873 | Williams | Aug 2002 | A1 |
20020116106 | Breed et al. | Aug 2002 | A1 |
20020126002 | Patchell | Sep 2002 | A1 |
20020126875 | Naoi et al. | Sep 2002 | A1 |
20020135468 | Bos et al. | Sep 2002 | A1 |
20030040864 | Stein | Feb 2003 | A1 |
20030070741 | Rosenberg et al. | Apr 2003 | A1 |
20030103142 | Hitomi et al. | Jun 2003 | A1 |
20030122930 | Schofield et al. | Jul 2003 | A1 |
20030125855 | Breed et al. | Jul 2003 | A1 |
20030128106 | Ross | Jul 2003 | A1 |
20030137586 | Lewellen | Jul 2003 | A1 |
20030191568 | Breed | Oct 2003 | A1 |
20030202683 | Ma et al. | Oct 2003 | A1 |
20030209893 | Breed et al. | Nov 2003 | A1 |
20030222982 | Hamdan et al. | Dec 2003 | A1 |
20040016870 | Pawlicki et al. | Jan 2004 | A1 |
20040021947 | Schofield et al. | Feb 2004 | A1 |
20040022416 | Lemelson et al. | Feb 2004 | A1 |
20040086153 | Tsai et al. | May 2004 | A1 |
20040096082 | Nakai et al. | May 2004 | A1 |
20040146184 | Hamza et al. | Jul 2004 | A1 |
20040148063 | Patchell | Jul 2004 | A1 |
20040164228 | Fogg et al. | Aug 2004 | A1 |
20040200948 | Bos et al. | Oct 2004 | A1 |
20050036325 | Furusawa et al. | Feb 2005 | A1 |
20050073853 | Stam | Apr 2005 | A1 |
20050131607 | Breed | Jun 2005 | A1 |
20050219852 | Stam et al. | Oct 2005 | A1 |
20050226490 | Phillips et al. | Oct 2005 | A1 |
20050237385 | Kosaka et al. | Oct 2005 | A1 |
20060018511 | Stam et al. | Jan 2006 | A1 |
20060018512 | Stam et al. | Jan 2006 | A1 |
20060050018 | Hutzel et al. | Mar 2006 | A1 |
20060091813 | Stam et al. | May 2006 | A1 |
20060095175 | deWaal et al. | May 2006 | A1 |
20060103727 | Tseng | May 2006 | A1 |
20060250224 | Steffel | Nov 2006 | A1 |
20060250501 | Wildmann et al. | Nov 2006 | A1 |
20070024724 | Stein et al. | Feb 2007 | A1 |
20070104476 | Yasutomi et al. | May 2007 | A1 |
20070109406 | Schofield et al. | May 2007 | A1 |
20070115357 | Stein et al. | May 2007 | A1 |
20070120657 | Schofield et al. | May 2007 | A1 |
20070154063 | Breed | Jul 2007 | A1 |
20070154068 | Stein et al. | Jul 2007 | A1 |
20070193811 | Breed et al. | Aug 2007 | A1 |
20070221822 | Stein et al. | Sep 2007 | A1 |
20070229238 | Boyles et al. | Oct 2007 | A1 |
20070230792 | Shashua et al. | Oct 2007 | A1 |
20070242339 | Bradley | Oct 2007 | A1 |
20080036576 | Stein et al. | Feb 2008 | A1 |
20080043099 | Stein et al. | Feb 2008 | A1 |
20080137908 | Stein et al. | Jun 2008 | A1 |
20080147321 | Howard et al. | Jun 2008 | A1 |
20080231710 | Asari et al. | Sep 2008 | A1 |
20080234899 | Breed et al. | Sep 2008 | A1 |
20080239393 | Navon | Oct 2008 | A1 |
20080266396 | Stein | Oct 2008 | A1 |
20090052003 | Schofield et al. | Feb 2009 | A1 |
20090066065 | Breed et al. | Mar 2009 | A1 |
20090113509 | Tseng et al. | Apr 2009 | A1 |
20090143986 | Stein et al. | Jun 2009 | A1 |
20090182690 | Stein | Jul 2009 | A1 |
20090190015 | Bechtel et al. | Jul 2009 | A1 |
20090201137 | Weller et al. | Aug 2009 | A1 |
20090243824 | Peterson et al. | Oct 2009 | A1 |
20090256938 | Bechtel et al. | Oct 2009 | A1 |
20090300629 | Navon et al. | Dec 2009 | A1 |
20100125717 | Navon | May 2010 | A1 |
20100172547 | Akutsu | Jul 2010 | A1 |
20110018700 | Stein et al. | Jan 2011 | A1 |
20110219217 | Sixsou et al. | Sep 2011 | A1 |
20110280495 | Sixsou et al. | Nov 2011 | A1 |
20110307684 | Kreinin et al. | Dec 2011 | A1 |
20120002053 | Stein et al. | Jan 2012 | A1 |
20120045112 | Lundblad et al. | Feb 2012 | A1 |
20120056735 | Stein et al. | Mar 2012 | A1 |
20120069185 | Stein | Mar 2012 | A1 |
20120105639 | Stein et al. | May 2012 | A1 |
20120140076 | Rosenbaum et al. | Jun 2012 | A1 |
20120200707 | Stein et al. | Aug 2012 | A1 |
20120212593 | Na'aman et al. | Aug 2012 | A1 |
20120233841 | Stein | Sep 2012 | A1 |
20120314071 | Rosenbaum et al. | Dec 2012 | A1 |
20130135444 | Stein et al. | May 2013 | A1 |
20130141580 | Stein et al. | Jun 2013 | A1 |
20130147957 | Stein | Jun 2013 | A1 |
20130169536 | Wexler et al. | Jul 2013 | A1 |
20130271584 | Wexler et al. | Oct 2013 | A1 |
20130308828 | Stein et al. | Nov 2013 | A1 |
20140015976 | DeLine et al. | Jan 2014 | A1 |
20140033203 | Dogon et al. | Jan 2014 | A1 |
20140049648 | Stein et al. | Feb 2014 | A1 |
20140082307 | Kreinin et al. | Mar 2014 | A1 |
20140093132 | Stein et al. | Apr 2014 | A1 |
20140122551 | Dogon et al. | May 2014 | A1 |
20140125799 | Bos et al. | May 2014 | A1 |
20140156140 | Stein et al. | Jun 2014 | A1 |
20140160244 | Berberian et al. | Jun 2014 | A1 |
20140161323 | Livyatan et al. | Jun 2014 | A1 |
20140198184 | Stein et al. | Jul 2014 | A1 |
Number | Date | Country |
---|---|---|
519193 | Aug 2011 | AT |
1008142 | Jan 1996 | BE |
1101522 | May 1981 | CA |
2392578 | May 2001 | CA |
2392652 | May 2001 | CA |
644315 | Jul 1984 | CH |
2074262 | Apr 1991 | CN |
2185701 | Dec 1994 | CN |
1104741 | Jul 1995 | CN |
2204254 | Aug 1995 | CN |
1194056 | Sep 1998 | CN |
1235913 | Nov 1999 | CN |
1383032 | Dec 2002 | CN |
102193852 | Sep 2011 | CN |
102542256 | Jul 2012 | CN |
1152627 | Aug 1963 | DE |
1182971 | Dec 1964 | DE |
1190413 | Apr 1965 | DE |
1196598 | Jul 1965 | DE |
1214174 | Apr 1966 | DE |
2064839 | Jul 1972 | DE |
3004247 | Aug 1981 | DE |
3040555 | May 1982 | DE |
31001855 | Aug 1982 | DE |
3240498 | May 1984 | DE |
3248511 | Jul 1984 | DE |
3433671 | Mar 1985 | DE |
3515116 | Oct 1986 | DE |
3528220 | Feb 1987 | DE |
3535588 | Apr 1987 | DE |
3601388 | Jul 1987 | DE |
3637165 | May 1988 | DE |
3636946 | Jun 1988 | DE |
3642196 | Jun 1988 | DE |
3734066 | Apr 1989 | DE |
3737395 | May 1989 | DE |
3838365 | Jun 1989 | DE |
3833022 | Apr 1990 | DE |
3839512 | May 1990 | DE |
3839513 | May 1990 | DE |
3937576 | May 1990 | DE |
3840425 | Jun 1990 | DE |
3844364 | Jul 1990 | DE |
9010196 | Sep 1990 | DE |
4015927 | Nov 1990 | DE |
3932216 | Apr 1991 | DE |
4007646 | Sep 1991 | DE |
4107965 | Sep 1991 | DE |
4111993 | Oct 1991 | DE |
4015959 | Nov 1991 | DE |
4116255 | Dec 1991 | DE |
4023952 | Feb 1992 | DE |
4130010 | Mar 1992 | DE |
4032927 | Apr 1992 | DE |
4133882 | Apr 1992 | DE |
4035956 | May 1992 | DE |
4122531 | Jan 1993 | DE |
4124654 | Jan 1993 | DE |
4137551 | Mar 1993 | DE |
4136427 | May 1993 | DE |
4300941 | Jul 1993 | DE |
4206142 | Sep 1993 | DE |
4214223 | Nov 1993 | DE |
4231137 | Feb 1994 | DE |
4328304 | Mar 1994 | DE |
4328902 | Mar 1994 | DE |
4332612 | Apr 1994 | DE |
4238599 | Jun 1994 | DE |
4337756 | Jun 1994 | DE |
4344485 | Jun 1994 | DE |
4304005 | Aug 1994 | DE |
4332836 | Sep 1994 | DE |
4407082 | Sep 1994 | DE |
4407757 | Sep 1994 | DE |
4411179 | Oct 1994 | DE |
4412669 | Oct 1994 | DE |
4418122 | Dec 1994 | DE |
4423966 | Jan 1995 | DE |
4336288 | Mar 1995 | DE |
4428069 | Mar 1995 | DE |
4434698 | Mar 1995 | DE |
4341409 | Jun 1995 | DE |
4446452 | Jun 1995 | DE |
69107283 | Jul 1995 | DE |
4403937 | Aug 1995 | DE |
19505487 | Sep 1995 | DE |
19518978 | Nov 1995 | DE |
069302975 | Dec 1996 | DE |
29703084 | Apr 1997 | DE |
29805142 | May 1998 | DE |
19755008 | Jul 1999 | DE |
19829162 | Jan 2000 | DE |
10237554 | Mar 2004 | DE |
000010251949 | May 2004 | DE |
4480341 | May 2005 | DE |
19530617 | Feb 2009 | DE |
0048492 | Mar 1982 | EP |
0049722 | Apr 1982 | EP |
0072406 | Feb 1983 | EP |
0169734 | Jan 1986 | EP |
0176615 | Apr 1986 | EP |
0202460 | Nov 1986 | EP |
0340735 | Nov 1989 | EP |
0341985 | Nov 1989 | EP |
0348691 | Jan 1990 | EP |
0353200 | Jan 1990 | EP |
0354561 | Feb 1990 | EP |
0360880 | Apr 1990 | EP |
0361914 | Apr 1990 | EP |
0387817 | Sep 1990 | EP |
0426503 | May 1991 | EP |
0433538 | Jun 1991 | EP |
0450553 | Oct 1991 | EP |
0454516 | Oct 1991 | EP |
0455524 | Nov 1991 | EP |
0459433 | Dec 1991 | EP |
473866 | Mar 1992 | EP |
0477986 | Apr 1992 | EP |
0479271 | Apr 1992 | EP |
0487100 | May 1992 | EP |
0487332 | May 1992 | EP |
0487465 | May 1992 | EP |
0492591 | Jul 1992 | EP |
0495508 | Jul 1992 | EP |
0496411 | Jul 1992 | EP |
0501345 | Sep 1992 | EP |
0505237 | Sep 1992 | EP |
0513476 | Nov 1992 | EP |
0514343 | Nov 1992 | EP |
0527665 | Feb 1993 | EP |
529346 | Mar 1993 | EP |
0532379 | Mar 1993 | EP |
0533508 | Mar 1993 | EP |
0550397 | Jul 1993 | EP |
0558027 | Sep 1993 | EP |
0564858 | Oct 1993 | EP |
0567059 | Oct 1993 | EP |
0582236 | Feb 1994 | EP |
0586857 | Mar 1994 | EP |
0588815 | Mar 1994 | EP |
0590588 | Apr 1994 | EP |
0591743 | Apr 1994 | EP |
0602962 | Jun 1994 | EP |
0605045 | Jul 1994 | EP |
0606586 | Jul 1994 | EP |
0617296 | Sep 1994 | EP |
0626654 | Nov 1994 | EP |
0640903 | Mar 1995 | EP |
0642950 | Mar 1995 | EP |
0654392 | May 1995 | EP |
0667708 | Aug 1995 | EP |
0677428 | Oct 1995 | EP |
0686865 | Dec 1995 | EP |
0687594 | Dec 1995 | EP |
0697641 | Feb 1996 | EP |
733252 | Sep 1996 | EP |
0756968 | Feb 1997 | EP |
0788947 | Aug 1997 | EP |
0830267 | Mar 1998 | EP |
0860325 | Aug 1998 | EP |
0874331 | Oct 1998 | EP |
0889801 | Jan 1999 | EP |
0893308 | Jan 1999 | EP |
0899157 | Mar 1999 | EP |
0913751 | May 1999 | EP |
0949818 | Oct 1999 | EP |
1022903 | Jul 2000 | EP |
1058220 | Dec 2000 | EP |
1065642 | Jan 2001 | EP |
1074430 | Feb 2001 | EP |
1115250 | Jul 2001 | EP |
1170173 | Jan 2002 | EP |
1236126 | Sep 2002 | EP |
1257971 | Nov 2002 | EP |
1359557 | Nov 2003 | EP |
1727089 | Nov 2006 | EP |
1741079 | Jan 2007 | EP |
1748644 | Jan 2007 | EP |
1754179 | Feb 2007 | EP |
1790541 | May 2007 | EP |
1806595 | Jul 2007 | EP |
1837803 | Sep 2007 | EP |
1887492 | Feb 2008 | EP |
1930863 | Jun 2008 | EP |
1978484 | Oct 2008 | EP |
2068269 | Jun 2009 | EP |
2101258 | Sep 2009 | EP |
2131278 | Dec 2009 | EP |
2150437 | Feb 2010 | EP |
2172873 | Apr 2010 | EP |
2187316 | May 2010 | EP |
2365441 | Sep 2011 | EP |
2377094 | Oct 2011 | EP |
2383679 | Nov 2011 | EP |
2383713 | Nov 2011 | EP |
2395472 | Dec 2011 | EP |
2431917 | Mar 2012 | EP |
2448251 | May 2012 | EP |
2463843 | Jun 2012 | EP |
2602741 | Jun 2013 | EP |
2605185 | Jun 2013 | EP |
2629242 | Aug 2013 | EP |
2674323 | Dec 2013 | EP |
2690548 | Jan 2014 | EP |
2709020 | Mar 2014 | EP |
2728462 | May 2014 | EP |
2250218 | Apr 2006 | ES |
2610401 | Aug 1988 | FR |
2641237 | Jul 1990 | FR |
2646383 | Nov 1990 | FR |
2674201 | Sep 1992 | FR |
2674354 | Sep 1992 | FR |
2687000 | Aug 1993 | FR |
2706211 | Dec 1994 | FR |
2721872 | Jan 1996 | FR |
914827 | Jan 1963 | GB |
1000265 | Aug 1965 | GB |
1008411 | Oct 1965 | GB |
1054064 | Jan 1967 | GB |
1098608 | Jan 1968 | GB |
1098610 | Jan 1968 | GB |
1106339 | Mar 1968 | GB |
1178416 | Jan 1970 | GB |
1197710 | Jul 1970 | GB |
2210835 | Jun 1989 | GB |
2233530 | Jan 1991 | GB |
2255649 | Nov 1992 | GB |
2261339 | May 1993 | GB |
2262829 | Jun 1993 | GB |
9310728 | Jul 1993 | GB |
2267341 | Dec 1993 | GB |
2271139 | Apr 1994 | GB |
2275452 | Aug 1994 | GB |
2280810 | Feb 1995 | GB |
2289332 | Nov 1995 | GB |
970014 | Jul 1998 | IE |
S5539843 | Mar 1980 | JP |
55156901 | Dec 1980 | JP |
S5685110 | Jul 1981 | JP |
S5871230 | Apr 1983 | JP |
58110334 | Jun 1983 | JP |
58122421 | Jul 1983 | JP |
59114139 | Jul 1984 | JP |
59127200 | Jul 1984 | JP |
S6047737 | Mar 1985 | JP |
6080953 | May 1985 | JP |
S6078312 | May 1985 | JP |
S60206746 | Oct 1985 | JP |
60240545 | Nov 1985 | JP |
S60219133 | Nov 1985 | JP |
S60255537 | Dec 1985 | JP |
S6141929 | Feb 1986 | JP |
S6185238 | Apr 1986 | JP |
S61105245 | May 1986 | JP |
S61191937 | Aug 1986 | JP |
6079889 | Oct 1986 | JP |
61-260217 | Nov 1986 | JP |
S61285151 | Dec 1986 | JP |
S61285152 | Dec 1986 | JP |
62001652 | Jan 1987 | JP |
S6221010 | Jan 1987 | JP |
S6226141 | Feb 1987 | JP |
62080143 | Apr 1987 | JP |
S6216073 | Apr 1987 | JP |
6272245 | May 1987 | JP |
S62115600 | May 1987 | JP |
62131837 | Jun 1987 | JP |
S62253543 | Nov 1987 | JP |
S62253546 | Nov 1987 | JP |
S62287164 | Dec 1987 | JP |
63811446 | Jan 1988 | JP |
63258236 | Oct 1988 | JP |
63258237 | Oct 1988 | JP |
63192788 | Dec 1988 | JP |
6414700 | Jan 1989 | JP |
01123587 | May 1989 | JP |
H1168538 | Jul 1989 | JP |
01242917 | Sep 1989 | JP |
H01233129 | Sep 1989 | JP |
H01265400 | Oct 1989 | JP |
H01275237 | Nov 1989 | JP |
H0268237 | Mar 1990 | JP |
02190978 | Jul 1990 | JP |
H236417 | Aug 1990 | JP |
H02212232 | Aug 1990 | JP |
H2117935 | Sep 1990 | JP |
H0314739 | Jan 1991 | JP |
H0374231 | Mar 1991 | JP |
03099952 | Apr 1991 | JP |
03266739 | May 1991 | JP |
H03246413 | Nov 1991 | JP |
03282707 | Dec 1991 | JP |
03282709 | Dec 1991 | JP |
03286399 | Dec 1991 | JP |
H03273953 | Dec 1991 | JP |
H042909 | Jan 1992 | JP |
H0410200 | Jan 1992 | JP |
04114587 | Apr 1992 | JP |
04127280 | Apr 1992 | JP |
04137014 | May 1992 | JP |
H04137112 | May 1992 | JP |
H04194827 | Jul 1992 | JP |
04239400 | Aug 1992 | JP |
04242391 | Aug 1992 | JP |
H04238219 | Aug 1992 | JP |
04250786 | Sep 1992 | JP |
04291405 | Oct 1992 | JP |
H04303047 | Oct 1992 | JP |
H0516722 | Jan 1993 | JP |
H0538977 | Feb 1993 | JP |
0577657 | Mar 1993 | JP |
05050883 | Mar 1993 | JP |
H05137144 | Jun 1993 | JP |
H05155287 | Jun 1993 | JP |
05189694 | Jul 1993 | JP |
H05172638 | Jul 1993 | JP |
05213113 | Aug 1993 | JP |
H05201298 | Aug 1993 | JP |
05244596 | Sep 1993 | JP |
H05229383 | Sep 1993 | JP |
05298594 | Nov 1993 | JP |
05313736 | Nov 1993 | JP |
H05297141 | Nov 1993 | JP |
06048247 | Feb 1994 | JP |
H0640286 | Feb 1994 | JP |
06076200 | Mar 1994 | JP |
H0672234 | Mar 1994 | JP |
06107035 | Apr 1994 | JP |
06113215 | Apr 1994 | JP |
06117924 | Apr 1994 | JP |
06150198 | May 1994 | JP |
H06162398 | Jun 1994 | JP |
H06174845 | Jun 1994 | JP |
H06191344 | Jul 1994 | JP |
06215291 | Aug 1994 | JP |
6227318 | Aug 1994 | JP |
06230115 | Aug 1994 | JP |
H06229739 | Aug 1994 | JP |
H06229759 | Aug 1994 | JP |
06247246 | Sep 1994 | JP |
6266825 | Sep 1994 | JP |
06267304 | Sep 1994 | JP |
06270733 | Sep 1994 | JP |
06274626 | Sep 1994 | JP |
06276524 | Sep 1994 | JP |
H06262963 | Sep 1994 | JP |
H06267303 | Sep 1994 | JP |
H06275104 | Sep 1994 | JP |
06295601 | Oct 1994 | JP |
H06289138 | Oct 1994 | JP |
H06293236 | Oct 1994 | JP |
05093981 | Nov 1994 | JP |
06310740 | Nov 1994 | JP |
06321007 | Nov 1994 | JP |
H06324144 | Nov 1994 | JP |
06337938 | Dec 1994 | JP |
06341821 | Dec 1994 | JP |
H06332370 | Dec 1994 | JP |
07002021 | Jan 1995 | JP |
07004170 | Jan 1995 | JP |
07025286 | Jan 1995 | JP |
H072022 | Jan 1995 | JP |
732936 | Feb 1995 | JP |
07032935 | Feb 1995 | JP |
07047878 | Feb 1995 | JP |
07052706 | Feb 1995 | JP |
H0737180 | Feb 1995 | JP |
H0740782 | Feb 1995 | JP |
H0746460 | Feb 1995 | JP |
07069125 | Mar 1995 | JP |
07078240 | Mar 1995 | JP |
H0764632 | Mar 1995 | JP |
H0771916 | Mar 1995 | JP |
H07057200 | Mar 1995 | JP |
H07078258 | Mar 1995 | JP |
07105496 | Apr 1995 | JP |
H07101291 | Apr 1995 | JP |
H07105487 | Apr 1995 | JP |
H07108873 | Apr 1995 | JP |
H07108874 | Apr 1995 | JP |
07125571 | May 1995 | JP |
07137574 | May 1995 | JP |
H07125570 | May 1995 | JP |
H730149 | Jun 1995 | JP |
H07141588 | Jun 1995 | JP |
H07144577 | Jun 1995 | JP |
07186818 | Jul 1995 | JP |
07192192 | Jul 1995 | JP |
06000927 | Aug 1995 | JP |
07242147 | Sep 1995 | JP |
H07239714 | Sep 1995 | JP |
H07249128 | Sep 1995 | JP |
H07280563 | Oct 1995 | JP |
H07315122 | Dec 1995 | JP |
H0840138 | Feb 1996 | JP |
H0840140 | Feb 1996 | JP |
H0843082 | Feb 1996 | JP |
H0844999 | Feb 1996 | JP |
H0850697 | Feb 1996 | JP |
H08138036 | May 1996 | JP |
08166221 | Jun 1996 | JP |
08235484 | Sep 1996 | JP |
H08320997 | Dec 1996 | JP |
02630604 | Apr 1997 | JP |
H0991596 | Apr 1997 | JP |
09330415 | Dec 1997 | JP |
10038562 | Feb 1998 | JP |
10063985 | Mar 1998 | JP |
H1090188 | Apr 1998 | JP |
10134183 | May 1998 | JP |
10171966 | Jun 1998 | JP |
H10222792 | Aug 1998 | JP |
10261189 | Sep 1998 | JP |
H1123305 | Jan 1999 | JP |
11069211 | Mar 1999 | JP |
11078737 | Mar 1999 | JP |
H1178693 | Mar 1999 | JP |
H1178717 | Mar 1999 | JP |
11250228 | Sep 1999 | JP |
H11259634 | Sep 1999 | JP |
11345392 | Dec 1999 | JP |
2000016352 | Jan 2000 | JP |
2000085474 | Mar 2000 | JP |
2000113374 | Apr 2000 | JP |
2000127849 | May 2000 | JP |
2000207575 | Jul 2000 | JP |
2000215299 | Aug 2000 | JP |
2000305136 | Nov 2000 | JP |
2000311289 | Nov 2000 | JP |
2001001832 | Jan 2001 | JP |
2001092970 | Apr 2001 | JP |
2001180401 | Jul 2001 | JP |
2001188988 | Jul 2001 | JP |
2001297397 | Oct 2001 | JP |
2001351107 | Dec 2001 | JP |
2002022439 | Jan 2002 | JP |
2002046506 | Feb 2002 | JP |
200274339 | Mar 2002 | JP |
2002079895 | Mar 2002 | JP |
2002084533 | Mar 2002 | JP |
2002099908 | Apr 2002 | JP |
2002109699 | Apr 2002 | JP |
2002175534 | Jun 2002 | JP |
2002211428 | Jul 2002 | JP |
2002341432 | Nov 2002 | JP |
2003030665 | Jan 2003 | JP |
200376987 | Mar 2003 | JP |
200383742 | Mar 2003 | JP |
3395289 | Apr 2003 | JP |
2003123058 | Apr 2003 | JP |
2003150938 | May 2003 | JP |
2003168197 | Jun 2003 | JP |
2003178397 | Jun 2003 | JP |
2003217099 | Jul 2003 | JP |
2003248895 | Sep 2003 | JP |
2003259361 | Sep 2003 | JP |
2003281700 | Oct 2003 | JP |
20041658 | Jan 2004 | JP |
2004032460 | Jan 2004 | JP |
2004146904 | May 2004 | JP |
2004336613 | Nov 2004 | JP |
2004355139 | Dec 2004 | JP |
2005182158 | Jul 2005 | JP |
200088351000 | Mar 1995 | KR |
1020010018981 | Oct 2002 | KR |
1004124340000 | Mar 2004 | KR |
336535 | Jul 1971 | SE |
1988009023 | Nov 1988 | WO |
1990004528 | May 1990 | WO |
1993000647 | Jan 1993 | WO |
1993004556 | Mar 1993 | WO |
1993010550 | May 1993 | WO |
1993011631 | Jun 1993 | WO |
1993021596 | Oct 1993 | WO |
1994019212 | Sep 1994 | WO |
1995018979 | Jul 1995 | WO |
1995023082 | Aug 1995 | WO |
1996002817 | Feb 1996 | WO |
1996015921 | May 1996 | WO |
1996018275 | Jun 1996 | WO |
199621581 | Jul 1996 | WO |
1986005147 | Sep 1996 | WO |
1996034365 | Oct 1996 | WO |
1996038319 | Dec 1996 | WO |
1997001246 | Jan 1997 | WO |
1997029926 | Aug 1997 | WO |
1997035743 | Oct 1997 | WO |
1997048134 | Dec 1997 | WO |
1998010246 | Mar 1998 | WO |
1998014974 | Apr 1998 | WO |
1999023828 | May 1999 | WO |
1999043242 | Sep 1999 | WO |
1999059100 | Nov 1999 | WO |
2000015462 | Mar 2000 | WO |
2001026332 | Apr 2001 | WO |
2001039018 | May 2001 | WO |
2001039120 | May 2001 | WO |
2001064481 | Sep 2001 | WO |
2001070538 | Sep 2001 | WO |
2001077763 | Oct 2001 | WO |
2001080068 | Oct 2001 | WO |
2001080353 | Oct 2001 | WO |
2002071487 | Sep 2002 | WO |
2003065084 | Aug 2003 | WO |
2003093857 | Nov 2003 | WO |
2004004320 | Jan 2004 | WO |
2004005073 | Jan 2004 | WO |
2005098751 | Oct 2005 | WO |
2005098782 | Oct 2005 | WO |
2008134715 | Nov 2008 | WO |
2013121357 | Aug 2013 | WO |
Entry |
---|
Ran et al., “Development of Vision-based Vehicle Detection and Recognition System for Intelligent Vehicles”, Department of Civil and Environmental Engineering, University of Wisconsin at Madison, 1999 TRB Annual Meeting, Nov. 16, 1998. |
Raphael et al., “Development of a Camera-Based Forward Collision Alert System”, SAE International, Apr. 12, 2011. |
Rayner et al., “I-Witness Black Box Recorder” Intelligent Transportation Systems Program, Final Report for ITS-IDEA Project 84, Nov. 2001. |
Redmill, “The OSU Autonomous Vehicle”, 1997. |
Regensburger et al., “Visual Recognition of Obstacles on Roads”, Intelligent Robots and Systems, Elsevier, 1994. |
Reichardt, “Kontinuierliche Verhaltenssteuerung eines autonomen Fahrzeugs in dynamischer Umgebung” Universitat Kaiserslautern Dissertation, Transation: Continuous behavior control of an autonomous vehicle in a dynamic environment, Jan. 1996. |
Reid, “Vision-based guidance of an agriculture tractor”, IEEE Control Systems Magazine, Apr. 30, 1987, Abstract. |
Reisman et al., “Crowd Detection in Video Sequences”, IEEE, Intelligent Vehicles Symposium, Jan. 1, 2004. |
Reexamination Control No. 90/007,519, dated Jun. 9, 2005, Reexamination of U.S. Pat. No. 6,222,447, issued to Schofield et al. |
Reexamination Control No. 90/011,478, dated Mar. 28, 2011, Reexamination of U.S. Pat. No. 6,222,447, issued to Schofield et al. |
Reexamination Control No. 90/007,520, dated Jun. 9, 2005, Reexamination of U.S. Pat. No. 5,949,331, issued to Schofield et al. |
Reexamination Control No. 90/011,477, dated Mar. 14, 2011, Reexamination of U.S. Pat. No. 5,949,331, issued to Schofield et al. |
Ritter et al., “Traffic sign recognition using colour information”, Math, Computing, Modelling, vol. 22, No. 4-7, pp. 149-161, Oct. 1995. |
Ritter, “Traffic Sign Recognition in Color Image Sequences”, Institute for Information Technology, 1992, pp. 12-17. |
Roberts, “Attentive Visual Tracking and Trajectory Estimation for Dynamic Scene Segmentation”, University of Southampton, PhD submission, Dec. 1994. |
Rombaut et al., “Dynamic data temporal multisensory fusion in the Prometheus ProLab2 demonstrator”, IEEE Paper, 1994. |
Ross, “A Practical Stereo Vision System”, The Robotics Institute, Carnegie Mellon University, Aug. 25, 1993. |
Rowell, “Applying Map Databases to Advanced Navigation and Driver Assistance Systems”, The Journal of Navigation 54.03 (2001): 355-363. |
Sahli et al., “A Kalman Filter-Based Update Scheme for Road Following,” IAPR Workshop on Machine Vision Applications, pp. 5-9, Nov. 12-14, 1996. |
Salvador et al., “Cast shadow segmentation using invariant color features”, Computer Vision and Image Understanding, vol. 95, 2004. |
Sanders, “Speed Racers: Study to monitor driver behavior to determine the role of speed in crashes”, Georgia Research Tech News, Aug. 2002. |
Sayer et al., “The Effect of Lead-Vehicle Size on Driver Following Behavior”, University of Michigan Transportation Research Institute, 2000-15, Jun. 2000. |
Schneiderman et al., “Visual Processing for Autonomous Driving,” IEEE Workshop on Applications of Computer Vision, Palm Springs, CA, Nov. 30-Dec. 2, 1992. |
Schonfeld et al., Compact Hardware Realization for Hough Based Extraction of Line Segments in Image Sequences for Vehicle Guidance, IEEE Paper, 1993, Abstract. |
Schumann et al., “An Exploratory Simulator Study on the Use of Active Control Devices in Car Driving,” No. IZF-1992-B-2. Institute for Perception RVO-TNO Soesterber (Netherlands), May 1992. |
Schwarzinger et al., “Vision-based car-following: detection, tracking, and identification”, Jul. 1, 1992. |
Scott, “Video Image on a Chip”, Popular Science, vol. 237, No. 3, Sep. 1991, pp. 50. |
Seelen et al., “Image Processing for Driver Assistance”, 1998. |
Seger et al., “Vision Assistance in Scenes with Extreme Contrast,” IEEE Micro, vol. 13, No. 1, Feb. 1993. |
Shafer, “Automation and Calibration for Robot Vision Systems”, National Science Foundation, Carnegie Mellon University Research Showcase, May 12, 1988. |
Shashua et al., “Two-body Segmentation from Two Perspective Views”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, pp. 263-270, Dec. 2001, Abstract. |
Shashua et al., “Direct Estimation of Motion and Extended Scene Structure from a Moving Stereo Rig”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 1998, pp. 211-218. |
Shashua et al., “Illumination and View Position in 3D Visual Recognition”, Advances in Neural Information Processing Systems, Morgan Kauffman Publishers, CA 1992 (Proc. of NIPS '91), pp. 404-411. |
Shashua et al., “Image-Based View Synthesis by Combining Trilinear Tensors and Learning Techniques”, ACM Conference on Virtual Reality and Systems (VRST), Sep. 1997, pp. 140-145. |
Shashua et al., “Novel View Synthesis by Cascading Trilinear Tensors”, IEEE Transactions on Visualization and Computer Graphics. vol. 4, No. 4, Oct.-Dec. 1998. |
Shashua et al., “On Degeneracy of Linear Reconstruction from Three Views: Linear Line Complex and Applications”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 21 (3), 1999, pp. 244-251. |
Shashua et al., “3D Reconstruction from Tangent-of-Sight”, European Conference on Computer Vision (ECCV), Jun. 2000, Dublin, Ireland, pp. 220-234. |
Shashua et al., “A Geometric Invariant for Visual Recognition and 3D Reconstruction From Two Perspective/Orthographic Views”, Proceedings of the IEEE 2nd Qualitative Vision Workshop, Jun. 1993, New York, NY, pp. 107-117. |
Shashua et al., “A Parallel Decomposition Solver for SVM: Distributed Dual Ascend using Fenchel Duality”, Conf. on Computer Vision and Pattern Recognition (CVPR), Jun. 2008, Anchorage, Alaska. |
Shashua et al., “A Unifying Approach to Hard and Probabilistic Clustering”, International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005. |
Shashua et al., “Affine 3-D Reconstruction from Two Projective Images of Independently Translating Planes”, International Conference on Computer Vision (ICCV), Jul. 2001, Vancouver, Canada, pp. 238-244. |
Shashua et al., “Algebraic Functions for Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) vol. 17(8), Jan. 1994 pp. 779-789. |
Shashua et al., “Ambiguity from Reconstruction From Images of Six Points”, International Conference on Computer Vision (ICCV), Jan. 1998, Bombay India, pp. 703-708. |
Shashua et al., “Convergent Message-Passing Algorithms for reference over General Graphs with Convex Free Energies”, Conf. on Uncertainty in AI (UAI), Helsinki, Jul. 2008. |
Shashua et al., “Doubly Stochastic Normalization for Spectral Clustering”, Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec. 2006. |
Shashua et al., “Duality of multi-point and multi-frame geometry: Fundamental shape matrices and tensors”, European Conference on Computer Vision (ECCV), Apr. 1996, Cambridge United Kingdom, pp. 217-227. |
Shashua et al., “Dynamic P.sup.n to P.sup.n Alignment”, In Handbook of Computational Geometry for Pattern Recognition, Computer Vision. Neuro computing and Robotics. Eduardo Bayro-Corrochano (eds.), Springer-Verlag, 2004. |
Shashua et al., “Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weight-based Approach”, Journal of Machine Learning Research (JMLR), 6(11):1885-1887, 2005, pp. 1885-1887. |
Shashua et al., “Grouping Contours by Iterated Pairing Network”, Advances in Neural Information Processing Systems 3, (Proc. of NIPS '90), Morgan Kaufmann Publishers, CA, 1991, pp. 335-341. |
Shashua et al., “Homography Tensors: On Algebraic Entities That Represent Three Views of Static or Moving Planar Points”, European Conference on Computer Vision (ECCV), Jun. 2000, Dublin, Ireland, pp. 163-177. |
Hessburg et al., “An Experimental Study on Lateral Control of a Vehicle,” California Partners for Advanced Transit and Highways (PATH), Jan. 1, 1991. |
Hillebrand et al., “High speed camera system using a CMOS image sensor”, IEEE Intelligent Vehicles Symposium., Oct. 3-5, 1999, pp. 656-661, Abstract. |
Ho et al., “Automatic spacecraft docking using computer vision-based guidance and control techniques”, Journal of Guidance, Control, and Dynamics, vol. 16, No. 2 Mar.-Apr. 1993. |
Hock et al., “Intelligent Navigation for Autonomous Robots Using Dynamic Vision”, XVIIth ISPRS Congress, pp. 900-915, Aug. 14, 1992. |
Holst, “CCD Arrays, Cameras, and Displays”, Second Edition, Bellingham, WA: SPIE Optical Engineering Press, 1998; pp. v-xxiii, 7-12, 45-101, and 176-179, excerpts. |
Honda Worldwide, “Honda Announces a Full Model Change for the Inspire.” Jun. 18, 2003. |
Horprasert et al., “A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection”, Proceeding of IEEE International Conference on Computer vision Frame—Rate Workshop, 1999. |
Hsieh et al., “Shadow elimination for effective moving object detection by Gaussian shadow modeling”, Image and Vision Computing, vol. 21, No. 6, 505-516, 2003. |
Hsieh et al., “A shadow elimination method for vehicle analysis”, Proceeding of IEEE International Conference on Pattern Recognition, vol. 4, 2004. |
Hu et al., “Action-based Road Horizontal Shape Recognition”, SBA Controle & Automacao, vol. 10, No. 2, May 1999. |
Huertgen et al., “Vehicle Environment Sensing by Video Sensors”, No. 1999-01-0932. SAE Technical Paper, 1999, Abstract. |
Huijsing, “Integrated smart sensors”, Sensors and Actuators A, vol. 30, Issues 1-2, pp. 167-174, Jan. 1992. |
Hutber et al., “Multi-sensor multi-target tracking strategies for events that become invisible” BMVC '95 Proc. of the 6th British conference on Machine vision, V2, 1995, pp. 463-472. |
IEEE 100—The Authoritative Dictionary of IEEE Standards Terms, 7.sup.th Ed. (2000). |
Ientilucci, “Synthetic Simulation and Modeling of Image Intensified CCDs (IICCD)”, Master Thesis for Rochester Inst. of Tech., Mar. 31, 2000. |
Ishida et al., “Development of a Driver Assistance System”, No. 2003-01-0279. SAE Technical Paper, 2002, Abstract. |
Ishihara et al., “Interline CCD Image Sensor with an Anti Blooming Structure,” IEEE International Solid-State Circuits Conference, Session XIII: Optoelectronic Circuits, THPM 13.6, Feb. 11, 1982. |
Ishikawa et al., “Visual Navigation of an Autonomous Vehicle Using White Line Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1988, Abst. |
Jaguar Press Releases Autumn 1991 “Jaguar Displays 21st Century Car Technologies”, Jaguar Communications & Public Affairs Dept. |
Janssen et al., “Hybrid Approach for Traffic Sign Recognition”, Program for a European Traffic with Highest Efficiency and Unprecedented Safety, Nov. 28, 1993. |
Japanese Article “Television Image Engineering Handbook, The Institute of Television Engineers of Japan”, Jan. 17, 1981. |
Jochem et al., “PANS: a portable navigation platform”, 1995 IEEE Symposium on Intelligent Vehicles, Detroit, MI, Sep. 25-26, 1995. |
Jochem et al., “Life in the Fast Lane”, AI Magazine, vol. 17, No. 2, pp. 11-50, Summer 1996. |
Johannes, “A New Microchip Ushers in Cheaper Digital Cameras”, The Wall Street Journal, Aug. 21, 1998, p. B1. |
Johnson, “Georgia State Patrol's In-Car Video System”, Council of State Governments, 1992, Abstract. |
Juberts et al., “Development and Test Results for a Vision-Based Approach to AVCS.” in Proceedings of the 26th International Symposium on Automotive Technology and Automation, Aachen, Germany, Sep. 1993, pp. 1-9. |
Kakinami et al., “Autonomous Vehicle Control System Using an Image Processing Sensor”, No. 950470. SAE Technical Paper, Feb. 1, 1995, Abstract. |
Kan et al., “Model-based vehicle tracking from image sequences with an application to road surveillance,” Purdue University, XP000630885, vol. 35, No. 6, Jun. 1996. |
Kang et al., “High Dynamic Range Video”, ACM Transactions on Graphics, vol. 22, No. 3, 2003. |
Kassel, “Lunokhod-1 Soviet Lunar Surface Vehicle”, Advanced Research Projects Agency, ARPA Order No. 189-1, Dec. 9, 1971. |
Kastrinaki et al., “A survey of video processing techniques for traffic applications”, Image and Computing 21, 2003. |
Kehtarnavaz et al., “Traffic sign recognition in noisy outdoor scenes”, 1995. |
Kehtarnavaz, “Visual control of an autonomous vehicle (BART)—the vehicle-following problem”, IEEE Transactions on Vehicular Technology, Aug. 31, 1991, Abstract. |
Kemeny et al., “Multiresolution Image Sensor,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 7, No. 4, Aug. 1997. |
Kenue et al., “LaneLok: Robust Line and Curve Fitting of Lane Boundaries”, Applications in Optical Science and Engineering, International Society for Optics and Photonics, 1993, Abstract. |
Kenue, “Lanelok: Detection of Lane Boundaries and Vehicle Tracking Using Image-Processing Techniques,” SPIE Conference on Mobile Robots IV, 1989. |
Kidd et al., “Speed Over Ground Measurement”, SAE Technical Paper Series, No. 910272, pp. 29-36, Feb.-Mar. 1991. |
Kiencke et al., “Automotive Serial controller Area Network,” SAE Technical Paper 860391, 1986, retrieved from http://papers.sae.org/860391/, accessed Mar. 20, 2015. |
Klassen et al., “Sensor Development for Agricultural Vehicle Guidance”, No. 932427. SAE Technical Paper, 1993, Abstract. |
Kluge et al., “Representation and Recovery of Road Geometry in YARF,” Carnegie Mellon University, Proceedings of the IEEE, pp. 114-119, 1992. |
Knipling, “IVHS Technologies Applied to Collision Avoidance: Perspectives on Six Target Crash Types and Countermeasures,” Technical Paper presented at Safety & Human Factors session of 1993 IVHS America Annual Meeting, Apr. 14-17, 1993, pp. 1-22. |
Knipling et al., “Vehicle-Based Drowsy Driver Detection: Current Status and Future Prospects,” IVHS America Fourth Annual Meeting, Atlanta, GA, Apr. 17-20, 1994, pp. 1-24. |
Koller et al., “Binocular Stereopsis and Lane Marker Flow for Vehicle Navigation: Lateral and Longitudinal Control,” University of California, Mar. 24, 1994. |
Kowalick, “Proactive use of highway recorded data via an event data recorder (EDR) to achieve nationwide seat belt usage in the 90th percentile by 2002” “Seat belt event data recorder (SB-EDR)” Transportation Recording: 2000 and Beyond., May 3-5, 1999, pp. 173-198, 369. |
Kozlowski et al., “Comparison of Passive and Active Pixel Schemes for CMOS Visible Imagers,” Proceedings of SPIE Conference on Infrared Readout Electronics IV, vol. 3360, Apr. 1998. |
Krotkov, “An agile stereo camera system for flexible image acquisition”, IEEE Journal on Robotics and Automation, Feb. 18, 1988. |
Kuan et al., “Autonomous Robotic Vehicle Road Following”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, No. 5, Sep. 1988, pp. 648-658, Abstract. |
Kuehnle, “Symmetry-based recognition of vehicle rears”, Pattern Recognition Letters 12, North-Holland, 1991. |
Kuhnert, “A vision system for real time road and object recognition for vehicle guidance,” in Proc. SPIE Mobile Robot Conf, Cambridge, MA, Oct. 1986, pp. 267-272. |
Kweon et al., “Behavior-Based Intelligent Robot in Dynamic Indoor Environments”, Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, Jul. 7-10, 1992. |
Xie et al., “Active and Intelligent Sensing of Road Obstacles: Application to the European Eureka-PROMETHEUS Project”, Fourth International Conference on Computer Vision, IEEE, 1993, Abstract. |
Xu et al., “3 DOF modular eye for smart car” School of Mechanical & Production Engineering Nanyang Technologies University, Intelligent Transportation Systems, 1999. Proc., Oct. 5-8, 1999, pp. 501-505. |
Xu et al., “Cast shadow detection in video segmentation”, Pattern Recognition Letters, vol. 26, Nov. 4, 2003. |
Yadid-Pecht et al., “Wide Intrascene Dynamic Range CMOS APS Using Dual Sampling,” IEEE Transactions on Electron Devices, vol. 44, No. 10, Oct. 1997. |
Yamada et al., “Wide Dynamic Range Vision Sensor for Vehicles,” 1994 Vehicle Navigation & Information Systems Conference Proceedings, pp. 405-408, 1994. |
Yazigi, “Technology: Promethean Plans for Next Generation of Cars”, The New York Times, Sep. 13, 1992. |
Yee, “Portable Camera Mount”, Feb. 1986, Abstract. |
Yeh et al., “Image-Based Dynamic Measurement for Vehicle Steering Control”, Proceedings of the Intelligent Vehicles 94 Symposium, 1994, Abstract. |
Yerazunis et al., “An inexpensive, all solid-state video and data recorder for accident reconstruction” Mitsubishi Technical Report TR-99-29 (presented at the 1999 SAE International Congress and Exposition, Detroit, MI, Mar. 3, 1999.), Apr. 24, 1999. |
Yoneyama et al., “Moving cast shadow elimination for robust vehicle extraction based on 2D joint vehicle/shadow models”, Proceeding of IEEE International Conference on Advanced Video and Signal Based Surveillance, 2003. |
Yoneyama et al., “Robust vehicle and traffic information extraction for highway surveillance”, EURASIP Journal on Applied Signal Processing, pp. 2305-2321, 2005. |
Young et al., “Cantata: Visual Programming Environment for the Khoros System, ACM SIGGRAPH Computer Graphics-Special focus: modular visualization environments (MVEs)”, vol. 29, issue 2, Mar. 16, 1995. |
Young et al., “Improved Obstacle Detection by Sensor Fusion”, IEEE Colloquium on “Prometheus and Drive”, Oct. 15, 1992, Abstract. |
Yu et al., “Vehicles Recognition by Video Camera” 1995. |
Yu, “Road tracking, lane segmentation and obstacle recognition by mathematical morphology,” Intelligent Vehicles '92 Symposium, Proceedings of the IEEE 1992 Conference, p. 166-172. |
Yuji et al., “Accidents and Near-Misses Analysis by Using Video Drive-Recorders in a Fleet Test”, Proceedings of the 17th International Technical Conference on the Enhanced Safety of Vehicles (ESV) Conference, Jun. 4-7, 2001 Amsterdam, TheNetherlands. National Highway Traffic Safety Administration, Washington, DC. HS 809 20, Jun. 2001. |
Zheng et al., “An Adaptive System for Traffic Sign Recognition,” IEEE Proceedings of the Intelligent Vehicles '94 Symposium, pp. 165-170 (Oct. 1994). |
Zidek, “Lane Position Tracking”, Aerospace and Electronics Conference, National Proceedings of the IEEE 1994, Abstract. |
Zigman, “Light Filters to Improve Vision”, Optometry and Vision Science, vol. 69, No. 4, pp. 325-328, Apr. 15, 1992. |
IPR Proceeding IPR2015-00950 filed Mar. 27, 2015 on U.S. Pat. No. 8,636,393. |
Najm, “Comparison of alternative crash-avoidance sensor technologies”, Jan. 6, 1995, Abstract. |
Nashman et al., “Real-time Visual Processing for Autonomous Driving,” in Proceedings of the IEEE Intelligent Vehicles, vol. 93, Jun. 1993, pp. 14-16. |
Nathan, Digital Video Data Handling, NASA JPL Tech Report 32-877, Pasadena, CA, Jan. 5, 1966. |
National Museum of Scotland archives regarding VVL's imputer photos. |
Navon, “SoC IP Qualification & Emulation Environment”, Dec. 8-9, 2004. |
Nguyen et al., “Obstacle detection using bi-spectrum CCD camera and image processing”, Proceedings of the Intelligent Vehicles '92 Symposium, Jun. 29-Jul. 1, 1992, p. 42-50. |
Nixon et al., “128.times. 128 CMOS Photodiode-Type Active Pixel Sensor With On-Chip Timing, Control and Signal Chain Electronics” 1995. |
Nixon et al., “256.times.256 CMOS Active Pixel Sensor Camera-on-a-Chip,” IEEE Journal of Solid-State Circuits, vol. 31, No. 12, Paper FA 11.1, 1996. |
No Hands Across America Journal, web page at http://www.cs.cmu.edu/.about.tjochem/nhaa/Journal.html. |
No Hands Across American Official Press Release web page at http://www.cs.cmu.edu/.about.tjochem/nhaa/official_press_release.html. |
Nolan, “Survey of Electronic Displays”, SAE Paper No. 750364, published Feb. 1, 1975. |
Oldenburg, “Comments on the Autronic Eye”, 2002. |
Ortega et al., “An Interactive, Reconfigurable Display System for Automotive Instrumentation”, SAE Paper No. 860173, published Mar. 1, 1986. |
Otsuka, “Flat Dot Matrix Display Module for Vehicle Instrumentation”, SAE Paper No. 871288, published Nov. 8, 1987. |
Pacaud et al., “Ground Speed Sensing,” Lucas International Symposium, Paris, France 1989. |
Paetzold, “Interpretation of visually sensed urban environment for a self-driving car” Ruhr-Universitat Bochum, Dissertation, Sep. 2000. |
Page et al., “Advanced technologies for collision avoidance,” Eureka on Campus (Summer 1992). |
Paradiso et al., “Wide-Range Precision Alignment for the Gem Muon System,” Oct. 1993. |
Paradiso, “Application of miniature cameras in video straightness monitor systems”, Draper Laboratory, Jun. 1994. |
Paradiso, “Electronics for precision alignment of the Gem Muon System”, Proceedings of the 1994 LeCroy Electronics for Future Colliders Conference, May 1994. |
Parent, “Automatic Driving for Small Public Urban Vehicles,” Intelligent Vehicles Symposium, Tokyo, Jul. 14-16, 1993. |
Parker (ed.), McGraw-Hill Dictionary of Scientific and Technical Terms Fifth Edition (1993). |
Parnell, “Reconfigurable Vehicle”. No. 2002-01-0144. SAE Technical Paper, 2002. Xilinx WPI 53, Nov. 19, 2001. |
Pelco Fixed Focal Length Lenses Product Specification, Apr. 1996. |
Peng et al., “Experimental Automatic Lateral Control System for an Automobile,” California Partners for Advanced Transit and Highways (PATH), Jan. 1, 1992. |
Peng, “Vehicle Lateral Control for Highway Automation,” Ph.D. Thesis—University of California Berkeley, 1992. |
Philips Components, PCA82C200, Stand-alone CAN-controller, Jan. 22, 1991. |
Philomin et al., “Pedestrain Tracking from a Moving Vehicle”, Proceedings of the IEEE, Intelligent Vehicles Symposium, IV, 2000. |
Photographs evidencing a Watec WAT-660D camera and photographs evidencing the mounting bracket used for attaching the WatecWAT-660D, the model of camera which was used as the forward facing camera on Navlab 6. |
Piccioli et al., “Robust road sign detection and recognition from image sequences”, 1994. |
Pollard, “Evaluation of the Vehicle Radar Safety Systems' Rashid Radar Safety Brake Collision Warning System”, U.S. Dept. of Transportation, National Highway Traffic Safety Administration, Feb. 29, 1988. |
Pomerleau, “Alvinn: An Autonomous Land Vehicle in a Neural Network”, Technical Report AIP-77 Department of Psychology, Carnegie Mellon University, Mar. 13, 1990. |
Pomerleau, “RALPH: Rapidly Adapting Lateral Position Handler”, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, pp. 506-511., 1995. |
Pomerleau et al., “Run-Off-Road Collision Avoidance Countermeasures Using IVHS Countermeasures TASK 3—vol. 1”, U.S. Dept. of Transportation, National Highway Traffic Safety Administration, Final Report, Aug. 23, 1995. |
Pomerleau et al., “Rapidly Adapting Machine Vision for Automated Vehicle Steering”, pp. 19-27, Apr. 30, 1996. |
Pomerleau, “Run-Off-Road Collision Avoidance Using Ivhs Countermeasures”, Robotics Institute, Task 6 Interim Report, Sep. 10, 1996. |
Porter et al., “Compositing Digital Images,” Computer Graphics (Proc. Siggraph), vol. 18, No. 3, pp. 253-259, Jul. 1984. |
Prasad, “Performance of Selected Event Data Recorders”, National Highway Traffic Safety Administration. Washington, DC, Sep. 2001. |
Prati et al., “Detecting moving shadows: algorithms and evaluation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, Jul. 1, 2003. |
Pratt, “Digital Image Processing, Passage—ED.3”, John Wiley & Sons, US, Jan. 1, 2001, pp. 657-659, XP002529771. |
Priese et al., “New Results on Traffic Sign Recognition”, IEEE Proceedings of the Intelligent Vehicles 1994 Symposium. |
Priese et al., “Traffic Sign Recognition Based on Color Image”, Universitat Koblenz-Landau, 1993, pp. 95-100. |
Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation, 1992. Power Electronics and Motion Control, Date of Conference Nov. 9-13, 1992. |
Proceedings of the Intelligent Vehicles Symposium, 1992-present. |
Proceedings of the Intelligent Vehicles Symposium, Tokyo, Jul. 14-16, 1993. |
Pynn et al., “Automatic identification of cracks in road surfaces” 7th International Conference on Image Processing and its Application, CP465, Jan. 1999, pp. 671-675, Abstract. |
Raboisson et al., “Obstacle Detection in Highway Environment by Colour CCD Camera and Image Processing Prototype Installed in a Vehicle”, Proceedings of the IEEE Intelligent Symposium 1994. |
Radatz, “The IEEE Standard Dictionary of Electrical and Electronics Terms,” Sixth Edition, Standards Coordinating Committee 10, Terms and Definitions, 1996. |
Raglan Tribe Video—1994; 1994; Raglan Tribe; “Robot Car Raglan Tribe” http://www.youtube.com/watch?v=AILZhcnpXYI. |
Ramesh et al., “Real-Time Video Surveillance and Monitoring for Automotive Applications”, SAE Technical Paper 2000-01-0347, Mar. 6, 2000, Abstract. |
Dickmanns et al.; “An integrated spatio-temporal approach to automatic visual guidance of autonomous vehicles,” EEE Transactions on Systems, Man, and Cybernetics, vol. 20, No. 6, Nov./Dec. 1990. |
Dickmanns, “Vehicles Capable of Dynamic Vision”, Aug. 23, 1997. |
Dickmanns, “4-D dynamic vision for intelligent motion control”, Universitat der Bundeswehr Munich, 1991. |
Dickmanns et al., “The seeing passenger car ‘VaMoRs-P’”, Oct. 24, 1994. |
Dingus et al., “TRAVTEK Evaluation Task C3—Camera Car Study” Final Report/ Sep. 1992-May 1994. Jun. 1995. |
Donnelly Panoramic Vision.TM. on Renault Talisman Concept Car at Frankfort Motor Show, PR Newswire, Frankfort, Germany Sep. 10, 2001. |
Doudoumopoulos et al., “CMOS Active Pixel Sensor Technology for High Performance Machine Vision Applications,” SME Applied Machine Vision '96—Emerging Smart Vision Sensors, Jun. 1996. |
Draves, “A Video Graphics Controller for Reconfigurable Automotive Displays”, No. 970193. SAE Technical Paper Feb. 24, 1997, Abstract. |
Dubrovin et al., “Application of real-time lighting simulation for intelligent front-lighting studies”, 2000 pp. 333-343. |
Dubuisson-Jolly, “Vehicle segmentation and classification using deformable templates”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Mar. 1996. |
Easton, “Jaguar Adapts Pilot's Night Sights for safer driving”, The Times, Sep. 28, 1991. |
Eaton, “Video Incident Capture System”, Technical Memorandum, OIC General Enforcement Branch, Sep. 1991. |
Eaton, “An RS-170 Camera for the Military Environment”, Proc. SPIE 0979, Airborne Reconnaissance XII, Feb. 23, 1989, Abstract. |
Eid et al., “A 256.times.256 CMOS Active Pixel Image Sensor,” Proceedings of SPIE: Charge-Coupled Devices and Solid State Optical Sensors V, vol. 2415, 1995. |
Elwell et al., “Near Infrared Spectroscopy,” accessed at http://www.ucl.ac.uk/medphys/research/borl/intro/nirs, Jan. 6, 1999. |
Ernst et al., “Camera calibration for lane and obstacle detection” Intelligent Transportation Systems, 1999 pp. 356-361. |
Fancher et al. “Intelligent Cruise Control Field Operational Test (Final Report)”, Final Report, vol. I: Technical Report, May 1998. |
Fancher et al., “Fostering Development, Evaluation, and Deployment of Forward Crash Avoidance Systems (FOCAS)” Annual Research Report DOT HS 808 437, May 1995. |
Ferryman et al., “Visual Surveillance for Moving Vehicles”, Secure Project, 2000. |
Fletcher, “CMOS light-sensor process makes possible low-cost smart machine-vision systems” Penton Media, Inc. et al., 1993. |
Forsyth, “A System for Finding Changes in Colour”, Oxford University, Jul. 23, 1987. |
Fossum, “Active Pixel Sensors: Are CCD's dinosaurs?” Proceedings of SPIE, Charge-Coupled Devices and Solid-State Optical Sensors III, vol. 1900, 1993. |
Fossum, “CMOS Active Pixel Sensor (APS) Technology for Multimedia Image Capture,” 1997 Multimedia Technology & Applications Conference (MTAC97), 1997. |
Fossum, “Low power camera-on-a-chip using CMOS active pixel sensor technology”, 1995 Symposium on Low Power Electronics, San Jose, CA, Oct. 9-10, 1995. |
Fowler et al., “A CMOS Area Image Sensor With Pixel-Level A/D Conversion,” Digest of Technical Papers of the 41st Solid-State Circuits Conference (ISSCC), 2001. |
Franke et al., “Autonomous driving approaches downtown”, IEEE Intelligent Systems, vol. 13, Nr. 6, 1999. |
French et al., “A comparison of IVHS progress in the United States, Europe, and Japan”, IVHA America, Dec. 31, 1993. |
Fujimori, “CMOS Passive Pixel Imager Design Techniques”, Massachusetts Institute of Technology, Ph.D. Dissertation for Electrical Engineering and Computer Science, Feb. 2002. |
Fung et al., “Effective moving cast shadow detection for monocular color image sequences”, The 11th International Conference on Image Analysis and Processing Proceedings, Palermo, Italy, Sep. 26-28, 2001,p. 404-409. |
Gat et al., “A Monocular Vision Advance Warning System for the Automotive Aftemarket”, Aftermarket SAE World Congress & Exhibition, No. 2005-01-1470. SAE Technical Paper, Jan. 1, 2005. |
Gavrila et al., “Real-Time Vision for Intelligent Vehicles” IEEE Instrumentation & Measurement Magazine, Jun. 2001, pp. 22-27. |
Gavrila, et al., “Real-time object detection for “smart” vehicles”, 1999. |
Geary et al., “Passive Optical Lane Position Monitor” Idea Project Final Report Contract ITS-24, Jan. 15, 1996. |
Gehrig, “Design, simulation, and implementation of a vision-based vehicle-following system” Doctoral Dissertation, Jul. 31, 2000. |
GEM Muon Review Meeting—SSCL Abstract; GEM TN-03-433, Jun. 30, 1993. |
Goesch et al., “The First Head Up Display Introduced by General Motors”, SAE Paper No. 890288, published Feb. 1, 1989. |
Goldbeck et al., “Lane detection and tracking by video sensors” Intelligent Transportation Systems, 1999. Proc., Oct. 5-8, 1999. |
Graefe et al., “Dynamic Vision for Precise Depth Measurement and Robot Control”, Computer Vision for Industry, Jun. 1993. |
Graefe, “Vision for Intelligent Road Vehicles”, Universitat de Bundeswehr Muchen, 1993, pp. 135-140. |
Greene et al., “Creating Raster Omnimax Images from Multiple Perspective Views Using the Elliptical Weighted Average Filter”, IEEE Computer Graphics and Applications, vol. 6, No. 6, pp. 21-27, Jun. 1986. |
Gruss et al., “Integrated sensor and range-finding analog signal processor”, IEEE Journal of Solid-State Circuits, vol. 26, No. 3, Mar. 1991. |
Gumkowski et al., “Reconfigurable Automotive Display System”, SAE Paper No. 930456 to Gumkowski, published Mar. 1, 1993. |
Hall, “Why I Dislike auto-Dimming Rearview Mirrors,” accessed at http://blog.consumerguide.com/why-i-dislike-autodimming-rearview-mirrors/- , Dec. 21, 2012. |
Hamit, “360-Degree Interactivity: New Video and Still Cameras Provide a Global Roaming Viewpoint”, Advanced Imaging, Mar. 1997, p. 50. |
Haritaoglu et al., “W4: Real-Time Surveillance of People and Their Activities”, IEEE Transactions Patter Analysis and Machine Intelligence, vol. 22, No. 8, Aug. 2000. |
Hebert et al., “3-D Vision Techniques for Autonomous Vehicles”, Defense Advanced Research Projects Agency, Carnegie Mellon University, Feb. 1, 1988. |
Hebert et al., “Local Perception for Mobile Robot Navigation in Natural Terrain: Two Approaches”, The Robotics Institute, Carnegie Mellon University, Abstract; Workshop on Computer Vision for Space Applications, Antibes, Sep. 22, 24, 1993, pp. 24-31. |
Hebert, “Intelligent unmanned ground vehicles: autonomous navigation research”, Carnegie Mellon (Kluwer Academic Publishers), Boston, 1997, Excerpt. |
Herbert et al., “3-D Vision Techniques for Autonomous Vehicles”, Technical Report, Carnegie Mellon University, Aug. 1988. |
Hess et al., “A Control Theoretic Model of Driver Steering Behavior,” IEEE Control Systems Magazine, vol. 10, No. 5, Aug. 1990, pp. 3-8. |
Broggi et al., “ARGO and the MilleMiglia in Automatico Tour”, IEEE Intelligent Systems, Jan.-Feb. 1999, pp. 55-64. |
Broggi et al., “Architectural Issues on Vision-based automatic vehicle guidance: The experience of the ARGO Project”, Academic Press, 2000. |
Broggi et al., “Automatic Vehicle Guidance: The Experience of the ARGO Vehicle”, World Scientific Publishing Co., 1999. |
Broggi et al., “Multi-Resolution Vehicle Detection using Artificial Vision,” IEEE Intelligent Vehicles Symposium of Jun. 14-17, 2004. |
Broggi et al., “Vision-based Road Detection in Automotive Systems: A real-time expectation-driven approach”, Journal of Artificial Intelligence Research, 1995. |
Broggi, “Robust Real-time Lane and Road Detection in Critical Shadow Conditions”, International Symposium on Computer Vision, IEEE, 1995, pp. 21-23. |
Brown, “A Survey of Image Registration Techniques”, vol. 24, ACM Computing Surveys, pp. 325-376, Dec. 4, 1992. |
Brown, “Scene Segmentation and Definition for Autonomous Robotic Navigation Using Structured Light Processing”, Doctoral Dissertation, University of Delaware, Army Science Conference Proceedings, Jun. 22-25, 1992, vol. 1, Dec. 31, 1988, pp. 189-203,Abstract. |
Brunelli et al., “Template Matching: Matched Spatial Filters and Beyond,” Pattern Recognition, vol. 30, No. 5, 1997. |
Bucher et al., “Image processing and behavior planning for intelligent vehicles”, IEEE Transactions on Industrial electronics 50.1 (2003): 62-75. |
Burger et al., “Estimating 3-D Egomotion from Perspective Image Sequences”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, No. 11, pp. 1040-1058, Nov. 1990. |
Burt et al., “A Multiresolution Spline with Application to Image Mosaics”, ACM Transactions on Graphics, vol. 2. No. 4, pp. 217-236, Oct. 1983. |
Cardiles, “Implementation de la commande d'un vehicule electrique autonome grace a un capteur de distance et d'angle base sur une camera lineaire” IUP de Mathematiques Appliquees et Industrielles, May 8, 1998. |
Carley et al., “Synthesis Tools for Mixed-Signal ICs: Progress on Frontend and Backend Strategies,” Proceedings of the 33rd Design Automation Conference, 1996. |
Cartledge, “Jaguar gives cat more lives”, Birmingham Post, Oct. 10, 1991. |
Cassiano et al., “Review of filtering methods in mobile vision from ground vehicles in low light conditions”, Proc. SPIE 1613, Mobile Robots VI, 322, Feb. 14, 1992. |
Chapuis et al., “Road Detection and Vehicles Tracking by Vision for an On-Board ACC System in the VELAC Vehicle”, 2000. |
Charkari et al., “A new approach for real time moving vehicle detection”, Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems, Yokohama, JP, Jul. 26-30, 1993. |
Chern et al., “The lane recognition and vehicle detection at night for a camera-assisted car on highway”, Robotics and Automation, 2003. Proceedings. ICRA'03. IEEE International Conference on. vol. 2. IEEE, 2003, Abstract. |
Chien et al., “Efficient moving object segmentation algorithm using background registration technique”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 12., No. 7, Jul. 2002. |
Clune et al., “Implementation and performance of a complex vision system on a systolic array machine”, Carnegie Mellon University, Jun. 15, 1987. |
CMOS sensor page of University of Edinburgh, 2015. |
Coghill, “Digital Imaging Technology 101”, Albert Theuwissen, Dalsa Corp, 2003. |
Coifman et al., “A real-time computer vision system for vehicle tracking and traffic surveillance”, Transportation Research Part C 6, pp. 271-288, 1998. |
Corsi, “Reconfigurable Displays Used as Primary Automotive Instrumentation”, SAE Paper No. 890282, published Feb. 1, 1989. |
Crisman et al., “Color Vision for Road Following”, Robotics Institute at Carnegie Mellon University, Proceedings of SPIE Conference on Mobile Robots Nov. 11, 1988, pp. 1-10, Oct. 12, 1988. |
Crisman et al., “UNSCARF, A Color Vision System for the Detection of Unstructured Roads” IEEE Paper 1991. |
Crisman et al., “Vision and Navigation—The Carnegie Mellon Navlab” Carnegie Mellon University, edited by Charles E. Thorpe, 1990. |
Crisman, “SCARF: Color vision system that tracks roads and intersections”, IEEE, 1993. |
Crossland, “Beyond Enforcement: In-Car Video Keeps Officers on the Streets”, Traffic technology international. Annual review, 1998, Abstract. |
Cucchiara et al., “Vehicle Detection under Day and Night Illumination”, Proceedings of 3rd International ICSC Symposium on Intelligent Industrial Automation (IIA 99), 1999. |
Cucchiara et al., “Detecting moving objects, ghosts, and shadows in video streams”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, No. 10, 2003. |
Cucchiara et al., “Improving Shadow Suppression in Moving Object Detection with HSV Color Information”, Proceeding of IEEE International Conference on Intelligent Transportation Systems, 2001. |
Curry et al., “The Lancashire telemedicine ambulance”, Journal of Telemedicine and telecare 4.4 (1998): 231-238, Dec. 1, 1998, Abstract. |
Dagan et al., “Forward collision warning with a single camera”, IEEE Intelligent Vehicles Symposium, 2004. |
Dally et al., “Digital Systems Engineering”, The University of Cambridge, United Kingdom, 1998. |
Davis et al., “Road Boundary Detection for Autonomous Vehicle Navigation”, Optical Engineering, vol. 25, No. 3, Mar. 1986, pp. 409-414. |
Davis, “Vision-Based Navigation for Autonomous Ground Vehicles” Defense Advanced Research Projects Agency, Jul. 18, 1988. |
De la Escalera et al., “Neural traffic sign recognition for autonomous vehicles” IEEE, 1994. |
De la Escalera et al., “Traffic sign recognition and analysis for intelligent vehicles”, Division of Systems Engineering and Automation, Madrid, Spain, 2003. |
Decision—Motions—Bd. R. 125(a), issued Aug. 29, 2006 in connection with Interference No. 105,325, which involved U.S. Appl. No. 09/441,341, filed Nov. 16, 1999 by Schofield et al. and U.S. Pat. No. 5,837,994, issued to Stam et al. |
DeFauw, “A System for Small Target Detection, Tracking, and Classification, Intelligent Transportation System”, Intelligent Transportation Systems, 1999. Proceedings. 1999 IEEE/IEEJ/JSAI International Conference on. IEEE, 1999, Abstract. |
Denes et al., “Assessment of driver vision enhancement technologies,” Proceedings of SPIE: Collusion Avoidance and Automated Traffic Management Sensors, vol. 2592, Oct. 1995. |
DeNuto et al., “LIN Bus and its Potential for use in Distributed Multiplex Applications”, SAE Technical Paper 2001-01-0072, Mar. 5-8, 2001. |
Denyer et al., “On-Chip CMOS Sensors for VLSI Imaging Systems”, Dept. of Elect. Engineering, University of Edinburgh, pp. 4b1.1-4b1.5, 1991. |
Derutin et al., “Real-time collision avoidance at road-crossings on board the Prometheus-ProLab 2 vehicle”, Intelligent Vehicles' 94 Symposium, Proceedings of the. IEEE, 1994, Abstract. |
Devlin, “The Eyellipse and Considerations in the Driver's Forward Field of View,” Society of Automotive Engineers, Inc., Detroit, MI, Jan. 8-12, 1968. |
Dickinson et al., “CMOS Digital Camera with Parallel Analog-to-Digital Conversion Architecture”, Apr. 1995. |
Dickmanns et al., “A Curvature-based Scheme for Improving Road Vehicle Guidance by Computer Vision,” University of Bundeswehr Munchen, 1986. |
Dickmanns et al., “Recursive 3-D road and relative ego-state recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, No. 2, Feb. 1992. |
Lasky et al., “Automated Highway Systems (AHS) Classification by Vehicle and Infrastructure”, AHMT Research Report, Jan. 25, 1994. |
Leachtenauer, “Resolution requirements and the Johnson criteria revisited,” Proceedings of SPIE, Infrared Imaging Systems: Design, Analysis, Modeling and Testing XIV, vol. 5076, 2003. |
LeBlanc et al., “CAPC: A Road-Departure Prevention System”, IEEE, Dec. 1996, pp. 61-71. |
Lee et al., “Automatic recognition of a car license plate using color image processing”, IEEE, Nov. 16, 1994. |
Lee, “How to Select a Heat Sink”, Electronics Cooling Magazine, Jun. 1, 1995. |
Leen et al., “Digital networks in the automotive vehicle”, Dec. 1999. |
Lezin, “Video Gear in Police Cruisers Gets Mixed Reviews Critics Say It Violates Privacy Rights and Inhibits Officers From Doing Their Jobs Well”, Mar. 17, 1997. |
Linkwitz, “High Precision Navigation: Integration of Navigational and Geodetic Methods,” Springer-Verlag, Jul. 5, 1989, Excerpt. |
Lisowski et al., “Specification of a small electric vehicle: modular and distributed approach,” IEEE 1997, pp. 919-924. |
Litkouhi et al., “Estimator and Controller Design for LaneTrak, a Vision-Based Automatic Vehicle Steering System,” Proceedings of the 32nd Conference on Decision and Control, San Antonio, Texas, Dec. 1993, pp. 1868-1873. |
Litwiller, “CCD vs. CMOS: Facts and Fiction,” Photonics Spectra, Jan. 2001. |
Liu Xianghong, “Development of a vision-based object detection and recognition system for intelligent vehicle”, 2000. |
Lockwood, “Design of an obstacle avoidance system for automated guided vehicles”, Doctoral thesis, University of Huddersfield, Oct. 1991. |
Lowenau et al., “Adaptive light control a new light concept controlled by vehicle dynamics and navigation”, SAE Technical Paper Series, Feb. 23-26, 1998. |
Lu et al., “On-chip Automatic Exposure Control Technique, Solid-State Circuits Conference”, ESSCIRC '91. Proceedings—17th European (vol. 1) Abst. Sep. 11-13, 1991. |
Lucas Demonstrates Intelligent Cruise Control, Detroit Feb. 27, 1995 available at; http://www.thefreelibrary.com/LUCAS+DEMONSTRATES+INTELLIGENT+CUISE+CONTR OL=a016602459. |
Luebbers et al., “Video-image-based neural network guidance system with adaptive view-angles for autonomous vehicles”, Applications of Artificial Neural Networks II. International Society for Optics and Photonics, 1991, Abstract. |
Lumia, “Mobile system for measuring retroreflectance of traffic signs”, Optics, Illumination, and Image Sensing for Machine Vision, Mar. 1, 1991, Abstract. |
Mackey et al., “Digital Eye-Witness Systems”, Transportation Recording: 2000 and Beyond, May 3-5, 1999, 271-284. |
Malik et al., “A Machine Vision Based System for Guiding Lane-change Maneuvers”, California Path Program, Institute of Transportation Studies, University of California, Berkeley, Sep. 1995. |
Manigel et al., “Computer control of an autonomous road vehicle by computer vision”—Industrial Electronics, Control and Instrumentation, Proceedings. IECON '91, 1991 International Conference on, p. 19-24 vol. 1, 1991. |
Manigel et al., “Vehicle control by computer vision,” Industrial Electronics, IEEE Transactions on, vol. 39, Issue 3, 181-188, Jun. 1992. |
Martel-Brisson et al., “Moving cast shadow detection from a Gaussian mixture shadow model”, Proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, 2005. |
Masaki, “Vision-based vehicle guidance”, Industrial Electronics, Control, Instrumentation, and Automation, 1992. Power Electronics and Motion Control, Proceedings of the 1992 International Conference on. IEEE, 1992. |
Mason et al., “The Golem Group I UCLA Autonomous Ground Vehicle in the DARPA Grand Challenge”, Jun. 12, 2006. |
Matthews, “Visual Collision Avoidance,” Oct. 1994, University of Southampton, PhD submission. |
Maurer, et al., “VaMoRs-P: an advanced platform for visual autonomous road vehicle guidance”, 1995. |
Maurer, “Flexible Automatisierung von StraBenfahrzeugen mit Rechnersehen” Universitat der Buneswehr Milnchen Dissertation, Jul. 27, 2000. |
MC68331 User's Manual, Freescale Semiconductor, Inc., 1994. |
McKenna et al., “Tracking Groups of People”, Computer Vision and Image Understanding, vol. 80, p. 42-56, 2000. |
McTamaney, “Mobile Robots Real-Time Intelligent Control”, FMC Corporation, Winter 1987. |
Mei Chen et al., “AURORA: A Vision-Based Roadway Departure Warning System, The Robotics Institute”, Carnegie Mellon University, published, Aug. 5-9, 1995. |
Mendis et al., “A 128.times.128 CMOS active pixel image sensor for highly integrated imaging systems”, Dec. 8, 1993. |
Mendis et al., “CMOS Active Pixel Image Sensor,” IEEE Transactions on Electron Devices, vol. 41, No. 3, Mar. 1994. |
Metzler, “Computer Vision Applied to Vehicle Operation”, Paper from Society of Automotive Engineers, Inc., 1988. |
Mikic et al., “Moving shadow and object detection in traffic scenes”, Proceeding of IEEE International Conference on Pattern Recognition, vol. 1, 2000. |
Miller, “Evaluation of vision systems for teleoperated land vehicles,” IEEE Control Systems Magazine, Jun. 28, 1988. |
Mimuro et al., “Functions and Devices of Mitsubishi Active Safety ASV” Proceedings of the 1996 IEEE Intelligent Vehicles Symposium, Sep. 19-20, 1996, Abstract. |
Mironer et al., “Examination of Single Vehicle Roadway Departure Crashes and Potential IVHS Countermeasures,” U.S. Department of Transportation, Aug. 1994. |
Miura et al., “Towards Vision-Based Intelligent Navigator: Its Concept and Prototype”, IEEE Transactions on Intelligent Transportation Systems, Jun. 2002. |
Miura et al., “Towards intelligent navigator that can provide timely advice on safe and efficient driving” Intelligent Transportation Systems Proceedings, Oct. 5-8, 1999, pp. 981-986. |
Mobileye N.V. Introduces EyeQ.TM. Vision System-On-A-Chip High Performance, Low Cost Breakthrough for Driver Assistance Systems, Detroit, Michigan, Mar. 8, 2004. |
Moini, “Vision Chips or Seeing Silicon,” Third Revision, Mar. 1997. |
Moravec, “Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover”, Computer Science Department, Stanford University, Ph.D. Thesis, Sep. 1980. |
Morgan et al., “Road edge tracking for robot road following: a real-time implementation,” vol. 8, No. 3, Aug. 1990. |
Mori et al., “Shadow and Rhythm as Sign patterns of Obstacle Detection”, Industrial Electronics, 1993. Conference Proceedings, ISIE'93—Budapest, IEEE International Symposium on. IEEE, 1993, Abstract. |
Morris, “E-Z-Pass and transmit using electronic toll tags for traffic monitoring” National Traffic Data Acquisition Conference, PDF pp. 54-63, 1996, 289-298, Abstract. |
Motorola Installation Guide, MVE162, Embedded Controller. |
Muirhead, “Developments in CMOS Camera Technology,” The Institution of Electrical Engineers, Dec. 5, 1994. |
Nadimi et al., “Physical models for moving shadow and object detection in video”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, No. 8, Aug. 2004. |
Thomanek et al., “Multiple object recognition and scene interpretation for autonomous road vehicle guidance” Oct. 1994. |
Thomas, “Real-time vision guided navigation”, Engineering Applications of Artificial Intelligence, Jan. 31, 1991, Abstract. |
Thongkamwitoon et al., “An adaptive real-time background subtraction and moving shadows detection”, Proceeding of IEEE International Conference on Multimedia and Expo. vol. 2, 2004. |
Thorpe et al., “Perception for Outdoor Navigation First Year Report”, Defense Advanced Research Projects Agency, Carnegie Mellong University, Dec. 31, 1990. |
Thorpe, “Vision and Navigation for the Carnegie-Mellon Navlab”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, No. 3, May 1998. |
Thorpe, “1988 Year End Report for Road Following at Carnegie Mellon”, Carnegie Mellon University, May 31, 1989. |
Thorpe et al., “Toward autonomous driving: the CMU Navlab. I. Perception”, IEEE Paper, Aug. 1991. |
Thorpe et al., “The 1997 Automated Highway Free Agent Demonstration”, 1997 pp. 496-501, 1997. |
Tokimaru et al., “CMOS Rear-View TV System with CCD Camera”, National Technical Report vol. 34, No. 3, pp. 329-336, Jun. 1988 (Japan). |
Toth et al., “Detection of moving shadows using mean shift clustering and a significance test”, Proceeding of IEEE International Conference on Pattern Recognition, vol. 4, 2004. |
Toyota Motor Corporation, “Present and future of safety technology development at Toyota.” 2004. |
Trainor et al., “Architectural Synthesis of Digital Signal Processing Algorithms Using ‘IRIS’”, Journal of VLSI Signal Processing Systems for Signal, Image and Video Technology, vol. 16, No. 1, 1997. |
Tremblay et al., “High resolution smart image sensor with integrated parallel analog processing for multiresolution edge extraction”, Robotics and Autonomous Systems 11, pp. 231-242, with abstract, 1993. |
Tribe et al., “Collision Avoidance,” Advances, Issue No. 4, May 1990. |
Tribe et al., “Collision Avoidance,” Lucas International Symposium, Paris, France, 1989. |
Tribe et al., “Collision Warning,” Autotech '93, Seminar 9, NEC Birmingham, UK, Nov. 1993. |
Tribe, “Intelligent Autonomous Systems for Cars, Advanced Robotics and; Intelligent Machines,” Peter Peregrinus, Nov. 1994. |
Trivdei et al., “Distributed Video Networks for Incident Detection and Management”, Computer Vision and Robotics Research Laboratory, 2000. |
Tsugawa et al., “An automobile with artificial intelligence,” in Proc. Sixth IJCAI, 1979. |
Tsugawa et al., “Vision-based vehicle in japan; machine vision systems and driving control systems”, IEEE Transactions on Industrial Electronics, vol. 41, No. 4, Aug. 1994. |
Tsutsumi et al., “Vehicle Distance Interval Control Technology” Mitsubishi Electric Advance, Technical Reports, vol. 78. pp. 10-12, Mar. 1997. |
Turk et al., “VITS—A Vision System for Autonomous Land Vehicle Navigation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, No. 3, May 3, 1988. |
Tzomakas and von Seelen, “Vehicle Detection in Traffic Scenes Using Shadows,” Internal report, Institut Fur Neuroinformatik Bochum, Internal Report Jun. 1998. |
Ulmer, “VITA II—active collision avoidance in real traffic” Proceedings of the Intelligent Vehicles '94 Symposium, Oct. 24-26, 1994, Abstract. |
Valeo Infos News, “Valeo's revolutionary Lane Departure Warning System makes debut on Nissan Infiniti vehicles”, 04.08 found at http://www.valeo.com/cwscontent/www.valeo.com/medias/fichiers/journaliste- s/en/CP/Idws_uk.pdf, Mar. 31, 2004. |
Van Leeuwen et al., “Motion Estimation with a Mobile Camera for Traffic Applications”, IEEE, US, vol. 1, pp. 58-63, Oct. 3, 2000. |
Van Leeuwen et al., “Motion Interpretation for In-Car Vision Systems”, IEEE, US, vol. 1, , p. 135-140, Sep. 30, 2002. |
Van Leeuwen et al., “Real-Time Vehicle Trackin in Image Sequences”, IEEE, US, vol. 3, pp. 2049-2054, XP010547308, May 21, 2001. |
Van Leeuwen et al., “Requirements for Motion Estimation in Image Sequences for Traffic Applications”, IEEE, pp. 354-359, XP002529773, 2000. |
Van Leeuwen et al., “Requirements for Motion Estimation in Image Sequences for Traffic Applications”, IEEE, US, vol. 1, 145-150, XP010340272, May 24, 1999. |
Vellacott, “CMOS in Camera,” IEE Review, pp. 111-114, May 1994. |
Vlacic et al., “Intelligent Vehicle Technologies, Theory and Applications”, Society of Automotive Engineers Inc., edited by SAE International, 2001. |
Vosselman et al., “Road traceing by profile matching and Kalman filtering”, Faculty of Geodetic Engineering, 1995. |
Wallace et al., “Progress in Robot Road-Following,” Proceedings of the 1986 IEEE International Conference on Robotics and Automation, vol. 3, pp. 1615-1621, 1986. |
Wan et al., “A New Edge Detector for Obstacle Detection with a Linear Stereo Vision System”, Proceedings of the Intelligent Vehicles '95 Symposium, Abstract. |
Wang et al., “CMOS Video Cameras”, article, 4 pages, University of Edinburgh, UK, 1991. |
Wang et al., “A probabilistic method for foreground and shadow segmentation”, Proceeding of IEEE International Conference on Image Processing, Pattern Recognition, vol. 3, Oct. 2, 2003. |
Wang, “Camera Calibration by Vanishing Lines for 3-D Computer Vision”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, No. 4, Apr. 15, 1991. |
Watec WAT-660D data sheet, found at http://www.wateccameras.com/products.php?prod_id=214. |
Web page at http://www.glassrack.net/potrsp1919192.html?utm_source=googlepepla&utm_me-dium=adwords&id=116297830341. |
Webpage: http://parts.royaloakschevy.com/showAssembly.aspx?makeName=pontiac&modelYear=1990&modelName=trans-sport&ukey_assembly=5888560&ukey_category=53643&assembly=921201mu10-009mu10-009. |
Weisser et al., “Autonomous driving on vehicle test tracks: Overview, implementation and vehicle diagnosis” Intelligent Transportation Systems, pp. 62-67, Oct. 5-8, 1999, Abstract. |
Wierwille et al., “Research on Vehicle-Based Driver Status/Performance Monitoring, Part III” Final Report, Sep. 1996. |
Wilson, “Technology: A little camera with big ideas—The latest smart vision system,” Financial Times, Jun. 17, 1993. |
Wolberg, Digital Image Warping, IEEE Computer Society Press, 1990. |
Wolberg, “A Two-Pass Mesh Warping Implementation of Morphing,” Dr. Dobb's Journal, No. 202, Jul. 1993. |
Wordenweber, “Driver assistance through lighting.” ESV: 17th International Technical Conference on the Enhanced Safety of Vehicles. Report. No. 476. 2001. |
Wright, “Take your hands off that car!”, Edn. vol. 42, No. 26, Dec. 18, 1997, Abstract. |
Wuller et al., “The usage of digital cameras as luminance meters”, Proc. SPIE 6502, Digital Photography III, 65020U, Feb. 20, 2007; doi: 1031117/12.703205. |
Wyatt et al., “Analog VLSI systems for Image Acquisition and Fast Early Vision Processing”, International Journal of Computer Vision, 8:3, pp. 217-223, 1992. |
Shashua et al., “Trajectory Triangulation: 3D Reconstruction of Moving Points from a Monocular Image Sequence”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 22(4), 2000, pp. 348-357. |
Shashua et al., “Trilinear Tensor: The Fundamental Construct of Multiple-view Geometry and its Applications”, International Workshop on Algebraic Frames for the Perception Action Cycle (AFPAC97), Kiel Germany, Sep. 8-9, 1997. Proceedings appeared inSpringer-Verlag, LNCS series, 1997, 190-206. |
Shashua et al., “Trilinearity in Visual Recognition by Alignment”, European Conference on Computer Vision (ECCV), May 1994, Stockholm, Sweden, pp. 479-484. |
Shashua et al., “Projective Depth: A Geometric Invariant for 3D Reconstruction From Two Perspective/Orthographic Views and for Visual Recognition,” International Conference on Computer Vision (ICCV), May 1993, Berlin, Germany, pp. 583-590. |
Shashua et al., “The Quotient Image: Class Based Recognition and Synthesis Under Varying Illumination Conditions”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 1999, pp. 566-573. |
Shashua et al., “The Quotient Image: Class Based Re-rendering and Recognition With Varying Illuminations”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 23(2), 2001, pp. 129-139. |
Shashua et al., “Pedestrian Detection for Driving Assistance, Systems: Single-Frame Classification and System Level, Performance”, IEEE Intelligent Vehicles Symposium, Jan. 1, 2004. |
Shashua, “On the Relationship Between the Support Vector Machine for classification and Sparsified Fisher's Linear Discriminant,” Neural Processing Letters, 1999, 9(2): 129-139. |
Shimizu et al., “A moving image processing system for personal vehicle system”, Nov. 9, 1992, Abstract. |
Shirai, “Robot Vision”, Future Generation Computer Systems, 1985. |
Shladover et al., “Automatic Vehicle Control Developments in the PATH Program,” IEEE Transaction on Vehicular Technology, vol. 40, No. 1, Feb. 1991, pp. 114-130. |
Shladover, “Research and Development Needs for Advanced Vehicle Control Systems,” Micro, IEEE, vol. 13, No. 1, Feb. 1993, pp. 11-19. |
Shladover, “Highway Electrification and Automation,” California Partners for Advanced Transit and Highways (PATH), Jan. 1, 1992. |
Siala et al., “Moving shadow detection with support vector domain description in the color ratios space”, Proceeding of IEEE International Conference on Pattern Recognition. vol. 4, 2004. |
Siegle, “Autonomous Driving on a Road Network,” Proceedings of the Intelligent Vehicles '92 Symposium Detroit, Michigan, ISBN 0-7803-0747-X; Jun. 29-Jul. 1, 1992. |
Smith et al., “An Automotive Instrument Panel Employing Liquid Crystal Displays”, SAE Paper No. 770274, published Feb. 1, 1977. |
Smith et al., “Optical sensors for automotive applications”, May 11, 1992. |
Smith et al., “Vision sensing for intelligent vehicle and highway systems”, Proceedings of the 1994 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Las Vegas, NV, Oct. 5, 1994. |
Soatto et al., “The Golem Group/University of California at Los Angeles Autonomous Ground Vehicle in the DARPA Grand Challenge”, Journal of Field Robotics 23(8), 2006, pp. 527-553. |
Solder et al., “Visual Detection of Distant Objects”, Intelligent Robots and Systems' 93, IROS'93. Proceedings of the 1993 IEEE/RSJ International Conference on. vol. 2. IEEE, 1993, Abstract. |
Sole et al., “Solid or not solid: vision for radar target validation”, IEEE Intelligent Vehicles Symposium, 2004. |
Sony Operating Manual CCD Color Video Camera Model: DXC-151A, 1993. |
Sony Specifications Single Chip CCD Color Video Camera DXC-151A. |
Sparks et al., “Multi-Sensor Modules with Data Bus Communication Capability” SAE Technical Paper 1999-01-1277, Mar. 1, 1999, doi: 10.4271/1999-01-1277, http://papers.sae.org/1999-01-1277/, Abstract. |
Bridhar, “Multirate and event-driven Kalman filters for helicopter flight”, IEEE Control Systems, Aug. 15, 1993. |
Standard J2284/3, “High-Speed Can (HSC) for Vehicle Applications at 500 Kbps, ” issued May 30, 2001. |
Stauder et al., “Detection of moving cast shadows for object segmentation”, IEEE Transactions on Multimedia, vol. 1, No. 1, Mar. 1999. |
Stein et al., “A Computer Vision System on a Chip: a case study from the automotive domain”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. |
Stein et al., “Challenges and solutions for Bundling Multiple DAS Applications on a Single Hardware Platform”, Procs. Vision 2008. |
Stein et al., “Direct Methods for Estimation of Structure and Motion from three views”, A.I. Memo No. 1594, MA Inst. of Tech., Nov. 1996. |
Stein et al., “Internal Camera Calibration using Rotation and Geometric Shapes”, Submitted to the Dept. of Electrical Engineering and Computer Science at MA Inst. of Tech., Masters Thesis, M.I.T., Feb. 1993. |
Stein et al., “Model-based brightness constraints: on direct estimation of structure and motion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, Issue 9, Sep. 2000. |
Stein et al., “Stereo-assist: Top-down stereo for driver assistance systems”, IEEE Intelligent Vehicles Symposium, 2010. |
Stein et al., “Vision-based ACC with a single camera: bounds on range and range rate accuracy”, IEEE Intelligent Vehicles Symposium, 2003. |
Stein et al., “A robust method for computing vehicle ego-motion”, Proceedings of the IEEE Intelligent Vehicles Symposium, 2000. |
Stein, “Accurate Internal Camera Calibration using Rotation, with Analysis of Sources of Error”, Computer Vision, Proceedings Fifth International Conference on. IEEE, 1995. |
Stein, “Geometric and photometric constraints: motion and structure from three views”, Mass. Inst. of Tech., Doctoral Dissertation, 1998. |
Stein, “Lens Distortion Calibration Using Point Correspondences”, A.I. Memo No. 1595, M.I.T. Artificial Intelligence Laboratory, Nov. 1996. |
Stein, “Tracking from multiple view points: Self-calibration of space and time”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Jun. 1999. |
Stein et al., “Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame,” A.I. Memo No. 1655, M.I.T. Artificial Intelligence Laboratory, Apr. 1999. |
Steiner et al., “Future applications or microsystem technologies in automotive safety systems” Advanced Microsystems for Automotive Applications '98, 1998, pp. 21-42. |
Stengel et al., “Intelligent Guidance for Headway and Lane Control”, Princeton University, Department of Mechanical and Aerospace Engineering, New Jersey, 1989. |
Stickford, “Candid cameras come to Park”, Grosse Pointe News, Mar. 7, 1996. |
Stiller et al., “Multisensor obstacle detection and tracking”, Image and Vision Computing 18, Elsevier, 2000, pp. 389-396. |
Sukthankar, “RACCOON: a Real-time Autonomous Car Chaser Operating Optimally at Night”, Oct. 1992. |
Sun et al., “On-road vehicle detection using optical sensors: a review”, 2004. |
Sun et al., “A Real-time Precrash Vehicle Detection System”, 2002. |
Szeliski, Image Mosaicing for Tele-Reality Applications, DEC Cambridge Research Laboratory, CRL 94/2, May 1994. |
Taktak et al., “Vehicle detection at night using image processing and pattern recognition”, Centre de Recherche en Automatique de Nancy, 1994. |
Taylor, “CCD and CMOS Imaging Array Technologies: Technology Review,” Xerox Research Centre Europe, Technical Report EPC-1998-106, 1998. |
“Generation of Vision Technology,” published by VLSI Vision Limited, pub. date unknown. |
“All-seeing screens for tomorrow's cars”, Southend Evening Echo, Oct. 4, 1991. |
“CCD vs. CMOS,” Teledyne DALSA Inc., accessed at https://www.teledynedalsa.com/imaging/knowledgecenter/appnotes/ccd-vs-cmos/. |
“Final Report of the Working Group on Advanced Vehicle Control Systems (AVCS)” Mobility 2000, Mar. 1990. |
“How an Image Intensifier Tube Works,” Photonis Group, accessed at http://www.nightvision.nl/faq-reader/how-does-an- image-intensifier-work.html. |
“Image intensified CCD high speed cameras,” Stanford Computer Optics, Inc., accessed at http://www.stanfordcomputeroptics.com/technology/iccd-systemoverview.html. |
“Magic Eye on safety”, Western Daily Press, Oct. 10, 1991. |
“On-screen technology aims at safer driving”, Kent Evening Post Oct. 4, 1991. |
“The Electromagnetic and Visible Spectra,” Light Waves and Color—Lesson 2, accessed at http://www.physicsclassroom.com/class/light/Lesson-2/The-Electromagnetic-and-Visible-Spectra. |
“Versatile LEDs Drive Machine vision in Automated Manufacture,” http://www.digikey.ca/en/articles/techzone/2012/jan/versatileleds-drive-machine-vision-in-automated-manufacture. |
3M, “Automotive Rear View Mirror Button Repair System”, Automotive Engineered Systems Division, Jun. 1996. |
Abshire et al., “Confession Session: Learning from Others Mistakes,” 2011 IEEE International Symposium on Circuits and Systems (ISCAS), 2011. |
Achler et al., “Vehicle Wheel Detector using 2D Filter Banks,” IEEE Intelligent Vehicles Symposium of Jun. 2004. |
Ackland et al., “Camera on a chip”, Digest of Technical Papers of the 42nd Solid-State Circuits Conference (ISSCC), Paper TA 1.2, 1996. |
Alley, “Algorithms for automatic guided vehicle navigation and guidance based on Linear Image Array sensor data”, Masters or PhD. Thesis, Dec. 31, 1988. |
Altan, “LaneTrak: a vision-based automatic vehicle steering system”, Applications in Optical Science and Engineering. International Society for Optics and Photonics, 1993, Abstract. |
Amidi, “Integrated Mobile Robot Control”, M.S. Thesis, Carnegie Mellon University, May 1990. |
An et al., “Aspects of Neural Networks in Intelligent Collision Avoidance Systems for Prometheus”, JFIT 93, pp. 129-135, Mar. 1993. |
Arain et al., “Action planning for the collision avoidance system using neural networks”, Intelligent Vehicle Symposium, Tokyo, Japan, Jul. 1993. |
Arain et al., “Application of Neural Networks for Traffic Scenario Identification”, 4th Prometheus Workshop, University of Compiegne, Paris, France, pp. 102-111, Sep. 1990. |
Ashley, “Smart Cars and Automated Highways”, Mechanical Engineering 120.5 (1998): 58, Abstract. |
Aufrere et al., “A model-driven approach for real-time road recognition”, Machine Vision and Applications 13, 2001, pp. 95-107. |
Auty et al., “Image acquisition system for traffic monitoring applications” IS&T/SPIE's Symposium on Electronic Imaging: Science & Technology. International Society for Optics and Photonics, Mar. 14, 1995. |
Aw et al., “A 128.times.128 Pixel Standard-CMOS Image Sensor with Electronic Shutter,” IEEE Journal of Solid-State Circuits, vol. 31, No. 12, Dec. 1996. |
Ballard et al., “Computer Vision”, 1982, p. 88-89, sect. 3.4.1. |
Barron et al., “The role of electronic controls for future automotive mechatronic systems”, IEEE/ASME Transactions on mechatronics 1.1, Mar. 1996, pp. 80-88. |
Batavia et al., “Overtaking vehicle detection using implicit optical flow”, Proceedings of the IEEE Transportation Systems Conference, Nov. 1997, pp. 729-734. |
Batavia, “Driver-Adaptive Lane Departure Warning Systems”, The Robotics Institute Camegie Mellon University Pittsburgh, Pennsylvania, 15213, Sep. 20, 1999. |
Bederson, “A miniature Space-Variant Active Vision System: Cortex-I”, Masters or Ph.D. Thesis, Jun. 10, 1992. |
Begault, “Head-Up Auditory Displays for Traffic Collision Avoidance System Advisories: A Preliminary Investigation”, Human Factors, 35(4), Dec. 1993, pp. 707-717. |
Behringer et al., “Simultaneous Estimation of Pitch Angle and Lane Width from the Video Image of a Marked Road,” pp. 966-973, Sep. 12-16, 1994. |
Behringer, “Road recognition from multifocal vision”, Intelligent Vehicles' 94 Symposium, Proceedings of the. IEEE, 1994, Abstract. |
Belt et al., “See-Through Turret Visualization Program”, No. NATICK/TR-02/005. Honeywell Inc., Minn, MN Sensors and Guidance Products, 2002. |
Bensmhair et al., “A cooperative approach to vision-based vehicle detection” Intelligent Transportation Systems, IEEE, 2001. |
Bertozzi et al., “Obstacle and lane detection on ARGO”, IEEE Transactions on Image Processing, 7(1):62-81, Jan. 1998, pp. 62-81. |
Bertozzi et al., “Performance analysis of a low-cost solution to vision-based obstacle detection”, Intelligent Transportation Systems, 1999. Proc., Oct. 5-8, 1999, pp. 350-355. |
Bertozzi et al., “Vision-based intelligent vehicles: State of the art and perspectives” Robotics and Autonomous Systems, 32, 2000 pp. 1-16. |
Bertozzi et al., “GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection”, IEEE transactions on image processing 7.1 (1998): 62-81. |
Betke et al., “Real-time multiple vehicle detection and tracking from a moving vehicle”, Machine Vision and Applications, 2000. |
Beucher et al., “Road Segmentation and Obstacle Detection by a Fast Watershed Transformation”, Intelligent Vehicles 94 Symposium, Proceedings of the. IEEE, 1994. |
Blomberg et al., “NightRider Thermal Imaging Camera and HUD Development Program for Collision Avoidance Applications”, Raytheon Commercial Infrared and ELCAN-Texas Optical Technologies, 2000, Abstract. |
Borenstein et al., “Where am I? Sensors and Method for Mobile Robot Positioning”, University of Michigan, Apr. 1996, pp. 2, 125-128. |
Bosch, “CAN Specification”, Version 2.0, Sep. 1991. |
Bow, “Pattern Recognition and Image Preprocessing (Signal Processing and Communications)”, CRC Press, Jan. 15, 2002, pp. 557-559. |
Brackstone et al., “Dynamic Behavioral Data Collection Using an Instrumented Vehicle”, Transportation Research Record: Journal of the Transportation Research Board, vol. 1689, Paper 99-2535, 1999. |
Brandt, “A CRT Display System for a Concept Vehicle”, SAE Paper No. 890283, published Feb. 1, 1989. |
Brauckmann et al., “Towards all around automatic visual obstacle sensing for cars”, Intelligent Vehicles' 94 Symposium, Proceedings of the. IEEE, 1994. |
Britell et al., “Collision avoidance through improved communication between tractor and trailer” Proceedings: International Technical Conference on the Enhanced Safety of Vehicles. vol. 1998. National Highway Traffic Safety Administration, 1998. |
Shashua et al., “Join Tensors: on 3D-to-3D Alignment of Dynamic Sets”, International Conference on Pattem Recognition (ICPR), Jan. 2000, Barcelona, Spain, pp. 99-102. |
Shashua et al., “Kernel Feature Selection with Side Data using a Spectral Approach”, Proc. of the European Conference on Computer Vision (ECCV), May 2004, Prague, Czech Republic. |
Shashua et al., “Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2003, Madison. |
Shashua et al., “Latent Model Clustering and Applications to Visual Recognition”, International Conference on Computer Vision (ICCV), Rio, Brazil, Oct. 2007. |
Shashua et al., “Learning over Sets using Kernel Principal Angles”, Journal of Machine Learning Research, 2003, pp. 913-931. |
Shashua et al., “Linear Image Coding for Regression and Classification using the Tensor-rank Principle”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Dec. 2001, Hawaii, pp. 42-49, Abstract. |
Shashua et al., “Manifold Pursuit: A New Approach to Appearance Based Recognition”, International Conference on Pattern Recognition (ICPR), Aug. 2002, Quebec, Canada. |
Shashua et al., “Multi-frame Infinitesimal Motion Model for the Reconstruction of (Dynamic) Scenes with Multiple Linearly Moving Objects”, International Conference on Computer Vision (ICCV), Jul. 2001,, Vancouver, Canada, pp. 592-599. |
Shashua et al., “Multiple View Geometry of Non-planar Algebraic Curves”, International Conference on Computer Vision (ICCV), Vancouver, Canada, Jul. 2001, pp. 181-189. |
Shashua et al., “Structural Saliency: the Detection of Globally Salient Structures Using a Locally Connected Network”, International Conference on Computer Vision (ICCV), Tarpon Springs, Florida, pp. 321-327, Jul. 1988. |
Shashua et al., “The Study of 3D-from-2D using Elimination”, International Conference on Computer Vision (ICCV), Jun. 1995, Boston, MA, pp. 473-479. |
Shashua et al., “Multiple-view Geometry and Photometry, In Recent Progress in Computer Vision”, Springer-Verlag, LNCS series, Invited papers of ACCV'95, Singapore Dec. 1995, 225-240, Abstract. |
Shashua et al., “Multiple-view geometry of general algebraic curves”, International Journal of Computer Vision (IJCV), 2004. |
Shashua et al., “Multi-way Clustering Using Super-symmetric Non-negative Tensor Factorization”, Proc. of the European Conference on Computer Vision (ECCV), Graz, Austria, May 2006. |
Shashua et al., “Nonnegative Sparse PCA”, Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec. 2006. |
Shashua et al., “Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision”, International Conference on Machine Learning (ICML), Bonn, Germany, Aug. 2005. |
Shashua et al., “Norm-Product Belief Propagation: Primal-Dual Message-Passing for Approximate Inference”, IEEE Trans. on Information Theory, Jun. 28, 2010. |
Shashua et al., “Novel View Synthesis in Tensor Space”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 1997, pp. 1034-1040. |
Shashua et al., “Off-road Path Following using Region Classification and Geometric Projection Constraints”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2006, NY. |
Shashua et al., “Omni-Rig Sensors: What Can be Done With a Non-Rigid Vision Platform?”, Workshop on Applications of Computer Vision (W ACV), pp. 174-179, Princeton, Oct. 1998, pp. 174-179. |
Shashua et al., “Omni-rig: Linear Self-recalibration of a Rig with Varying Internal and External Parameters,” International Conference on Computer Vision (ICCV), Jul. 2001, Vancouver, Canada, pp. 135-141. |
Shashua et al., “On calibration and reconstruction from planar curves”, European Conference on Computer Vision (ECCV), pp. 256-270, Jun. 2000, Dublin, Ireland, pp. 256-270. |
Shashua et al., “On Geometric and Algebraic Aspects of 3D Affine and Projective Structures from Perspective 2D Views”, In Applications of Invariance in Computer Vision, Springer-Verlag LNCS No. 825, 1994, 127-143. |
Shashua et al., “On Photometric Issues in 3D Visual Recognition from a Single 2D Image”, International Journal of Computer Vision (IJCV), 21(1/2), 1997 pp. 99-122. |
Shashua et al., “On Projection Matrices P.sup.k -P.sup.2, k=3, 6, and their Applications in Computer Vision”, International Journal of Computer Vision (IJCV), 2002, pp. 53-67. |
Shashua et al., “On the Reprojection of 3D and 2D Scenes Without Explicit Model Selection”, European Conference onf Computer Vision (ECCV), Jun. 2000, Dublin, Ireland, pp. 468-482. |
Shashua et al., “On the Structure and Properties of the Quadrifocal Tensor”, European Conference on Computer Vision (ECCV), Jun. 2000, Dublin, Ireland, pp. 354-368. |
Shashua et al., “On the Synthesis of Dynamic Scenes from Reference Views”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2000, pp. 133-139. |
Shashua et al., “pLSA for Sparse Arrays With Tsallis Pseudo-Additive, Divergence: Noise Robustness and Algorithm”, International Conference on Computer Vision (ICCV), Rio, Brazil, Oct. 2007. |
Shashua et al., “Principal Component Analysis Over Continuous Subspaces and Intersection of Half-spaces”, European Conference on Computer Vision (ECCV), May 2002, Copenhagen, Denmark, pp. 133-147. |
Shashua et al., “Probabilistic Graph and Hypergraph Matching”, Conf. on Computer Vision and Pattern Recognition (CVPR), Jun. 2008, Anchorage, Alaska. |
Shashua et al., “Projective Structure from Uncalibrated Images: Structure from Motion and Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (P AMI), (vol. 16(8), 1994, pp. 778-790. |
Shashua et al., “Q-warping: Direct Computation of Quadratic Reference Surfaces”, IEEE Transactions on Pattem Analysis and Machine Intelligence (P AMI), vol. 23(8), 2001, pp. 920-925. |
Shashua et al., “Relative Affine Structure: Canonical Model for 3D from 2D Geometry and Applications,” IEEE, Transactions on Pattem Analysis and Machine Intelligence (P AMI) vol. 18(9), pp. 873-883, Jun. 1994. |
Shashua et al., “Relative Affine Structure: Theory and Application for 3D Reconstruction From Perspective Views,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, pp. 483-489, Jun. 1994. |
Shashua et al., “Revisiting Single-view Shape Tensors: Theory and Applications,” EP Conference on Computer Vision (ECCV), Copenhagen, DK, pp. 256-270, May 2002. |
Shashua et al., “Robust Recovery of Camera Rotation from Three Frames,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, pp. 796-802, Jun. 1996. |
Shashua et al., “Shape Tensors for Efficient and Learnable Indexing”, Proceedings of the workshop on Scene Representations, Jun. 1995, Cambridge, MA, pp. 58-65. |
Shashua et al., “ShareBoost Efficient Multiclass Leaming with Feature Sharing, Neural Information and Processing Systems (NIPS)”, Dec. 2011. |
Shashua et al., “Sparse Image Coding using a 3D Non-negative Tensor Factorization”, International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005. |
Shashua et al., “Taxonomy of Large Margin Principle Algorithms for Ordinal Regression Problems”, Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec. 2002. |
Shashua et al., “Tensor Embedding of the Fundamental Matrix”, Kluwer Academic Publishers, Boston, MA, 1998. |
Shashua et al., “The Quadric Reference Surface: Applications in Registering Views of Complex 3D Objects”, European Conference on Computer Vision (ECCV), May 1994, Stockholm, Sweden, pp. 407-416. |
Shashua et al., “The Quadric Reference Surface: Theory and Applications”, 1994. |
Shashua et al., “The Rank 4 Constraint in Multiple (.gtoreq.3) View Geometry”, European Conference on Computer Vision (ECCV), Apr. 1996, Cambridge, United Kingdom, pp. 196-206. |
Shashua et al., “The Semi-Explicit Shape Model for Multi-object Detection and Classification”, Proc. of the European Conference on Computer Vision (ECCV), Crete, Greece, pp. 336-349, Sep. 2010. |
Shashua et al., “Threading Fundamental Matrices”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 23(1), Jan. 2001, pp. 73-77. |
Shashua et al., “Threading Kernel functions: on Bridging the Gap between Representations and Algorithms”, Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec. 2004. |
Shashua et al., “Time-varying Shape Tensors for Scenes with Multiply Moving Points”, IEEE Conference on Computer Vision and Pattern, pp. 623-630, Dec. 2001, Hawaii. |
Shashua et al., “Trajectory Triangulation over Conic Sections”, International Conference on Computer Vision (ICCV), Greece, 1999, pp. 330-337. |
Number | Date | Country | |
---|---|---|---|
20230249611 A1 | Aug 2023 | US |
Number | Date | Country | |
---|---|---|---|
60845381 | Sep 2006 | US | |
60837408 | Aug 2006 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 17814577 | Jul 2022 | US |
Child | 18297726 | US | |
Parent | 17451183 | Oct 2021 | US |
Child | 17814577 | US | |
Parent | 16948656 | Sep 2020 | US |
Child | 17451183 | US | |
Parent | 16125891 | Sep 2018 | US |
Child | 16948656 | US | |
Parent | 15262479 | Sep 2016 | US |
Child | 16125891 | US | |
Parent | 14164682 | Jan 2014 | US |
Child | 15262479 | US | |
Parent | 13887727 | May 2013 | US |
Child | 14164682 | US | |
Parent | 13452130 | Apr 2012 | US |
Child | 13887727 | US | |
Parent | 13173039 | Jun 2011 | US |
Child | 13452130 | US | |
Parent | 12377054 | US | |
Child | 13173039 | US |