Patent Grant
11829059
The present disclosure is directed to a scanning light imaging device in general, and more particularly, to a device that employs observed reflection of light beams from a remote surface or object to determine physical aspects of that surface and predict the subsequent position of the remote surface or object.
With the ubiquity of images that are available for display by an electronic device, the capabilities of a particular electronic device's display have become a significant factor to users. These images can include, movies, videos, podcasts, television, pictures, cartoons, illustrations, graphics, tables, charts, presentations, and the like. Also, the quality, resolution, and type of display for images that can be displayed by an electronic device is often the primary factor in a user's decision to purchase that particular electronic device. For example, users might prefer relatively low power projection displays for mobile devices, such as mobile telephones, notebook computers, hand held video game consoles, hand held movie players, personal digital assistants (PDA), and the like. These low power projection displays can include, and backlit or non-backlit Liquid Crystal Displays (LCD). Further, other relatively low power emissive displays such as Organic Light Emitting Diodes (OLED), are growing in popularity for mobile devices. Also, the size of a display for a mobile device is often limited to a relatively small area, i.e., displays that can easily fit in a hand or clothing pocket. The relatively small size of displays for many mobile devices can also limit their usability for some applications.
Stationary electronic devices, such as personal computers, televisions, monitors, and video game consoles, often employ high power projection display technologies, such as Gas Plasma, Cathode Ray Tubes (CRT), LCD, DLPs (Digital Light Processor), and the like. Also, displays for these relatively stationary electronic devices are often considerably larger than those displays employed with mobile devices, e.g., projection displays can be five feet across or more. However, the relatively large physical size of the cabinetry associated with most displays employed with stationary devices can be inconvenient and unattractive for many users, especially when the displays are not in use.
Front image projection devices can also be used to display images on a remote surface, e.g., a hanging screen of reflective fabric, or some other relatively vertical and reflective surface such as a wall. Also, a variety of different technologies are employed by front image projection devices, such as Digital Light Processors (DLP), Light Emitting Diodes (LED), Cathode Ray Tubes (CRT), Liquid Crystal Displays (LCD), Liquid Crystal on Silicon (LCoS), MicroElectroMechanicalSystems (MEMS) scanners, and the like. However, artifacts in reflections of beams of light projected onto remote surfaces or remote objects and determining a multi-dimensional position of the remote surfaces and/or remote objects have been difficult to compensate for, and often adversely affect the quality, resolution, and usability of reflections of these remotely projected beams of light.
Non-limiting and non-exhaustive embodiments of the present invention are described in reference to the following drawings. In the drawings, like reference numerals refer to like parts through all the various figures unless otherwise explicit.
For a better understanding of the present disclosure, a reference will be made to the following detailed description, which is to be read in association with the accompanying drawings, wherein:
The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show, by way of illustration, specific exemplary embodiments by which the invention may be practiced. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Among other things, the present invention may be embodied as methods or devices. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. The following detailed description is, therefore, not to be taken in a limiting sense.
Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. As used herein, the term “or” is an inclusive “or” operator, and is equivalent to the term “and/or,” unless the context clearly dictates otherwise. The term “based on” is not exclusive and allows for being based on additional factors not described, unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a,” “an,” and “the” include plural references. The meaning of “in” includes “in” and “on.”
The term “pseudorandom” as used herein, indicates a statistically random process, which appears to be random as distinguished from a truly random process, which lacks predictability. Pseudorandom processes may be generated using some deterministic elements combined with some non-repeating patterns. For example, a timestamp may be combined with the changing contents of a predetermined memory location to generate a pseudorandom number. Furthermore, this term as used herein, indicates lack of a predefined scanning organization, for example, an array of pixels (picture elements), parallel scanlines, hatched scanlines, cross hatched scanlines, open lissajous pattern scanlines, or any other arrangement or pattern having a temporal or spatial relationship between scanlines.
The term “twitchy pixel” or “binary pixel” as used herein, indicates a pixel that presents a binary state, e.g., either one or zero, in the presence or absence of photons. Further, the twitchy pixel can detect and indicate the exact moment of arrival of an individual photon impinging on the twitchy pixel by an immediate change in its binary state, e.g., from zero to one. In one or more embodiments, a Silicon Photon Multiplier (SiPM) array may be employed to provide an array of twitchy (binary) pixels. An individual SiPM pixel, is also known as a “Geiger mode APD” pixel that consists of a photodiode, across which a strong reverse bias voltage is applied. This “over bias voltage” is strong enough to ensure that an arriving photon not only causes a breakdown of the photodiode's natural directional resistance to current, but is also so strong that when one of the first arriving photons frees up a valence electron in the semiconductor lattice, this first freed electron, propelled by the strong local potential electric field force, rushes towards the positive photo diode junction, accelerates and through collisions within the lattice, causes other electrons to be freed setting up a chain reaction, resulting in a huge “avalanche” of conduction band electrons. In this way, a single blue or otherwise sufficiently energetic photon impinging on the SiPM pixel may cause as many as 200,000 electrons to “rush the gate”. “Energetic” photon energy may be construed as significantly greater than the semiconductor band gap between the valence band and the conductive band. For example, a highly energetic Blue 405 nm photon can 2.7 times or more of the energy required to jump across this bandgap. Thus, within as little as 100 picoseconds of the arrival of the first photons, a strong spike of current can be detected and used as fast reporting signal.
By arranging arrays of Geiger mode pixels, accurate and immediate avalanches may be used to precisely track the progression of a spot of light across the array, such as the trail of bubbles left by the rare occurrence of elementary particles in a bubble chamber used in particle physics. In this way, SiPM pixel arrays can have one of the highest photon detection efficiency (PDE), lowest dark noise, fast high-gain detection signal output with the lowest jitter which provide excellent time precision. For example, some pseudo random scanning laser spot tracking systems can employ such SiPM pixel arrays to track reflected spots of light in real time with high precision.
The term “corresponding” as used herein, may indicate a one-to-one, one-to-many, or many-to-one mapping. For example, an image pixel corresponding to a display position may indicate that the image pixel corresponds to more than one display position, when adjacent display positions are resolvable at a higher resolution in comparison with the resolution of the image associated with the image pixel. In such a case, a single image pixel may be interpolated or resolved to cover more than one display position, and thus, the single image pixel corresponds to more that one display position and indicates a one-to-many mapping. In another case where the image pixels and the display positions have substantially equal resolutions, the correspondence there between can be a one-to-one mapping. Furthermore, if a plurality of adjacent pixels have substantially equal values, they may be projected as a line to form the image instead of a series of individual positions on a display.
Examples of such systems that provide for pseudorandom scanning of light beams include, but are not limited to, those disclosed in U.S. Pat. No. 10,331,021 issued Jun. 25, 2019; U.S. Pat. No. 9,581,883 issued Feb. 28, 2017; U.S. Pat. No. 8,696,141 issued Apr. 15, 2014; U.S. Pat. No. 8,430,512 issued Apr. 30, 2013; U.S. Pat. No. 8,282,222 issued Oct. 9, 2012; all of which are incorporated herein by reference in their entirety.
The following briefly describes the embodiments of the invention to provide a basic understanding of some aspects of the invention. This brief description is not intended as an extensive overview. It is not intended to identify key or critical elements, or to delineate or otherwise narrow the scope. Its purpose is merely to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
Briefly described, the invention is directed to a scanning light imaging device for determining a position of a remote surface and/or remote object. displaying an image onto a remote surface. The scanning light imaging device employs a scanner to project image beams of visible and/or non-visible light, or image beams and tracer beams of light onto a remote surface/object, which reflects the projected beams of light. In one or more embodiments, image beams and/or tracer beams may be a spot formed by just one or more photons of light projected unto a remote surface and/or objects. Also, the image projection device may also employ a light detector to sense at least the reflections of light from the spot beams incident on the remote surface. In one or more embodiments, the scanning light imaging device employs the sensed tracer beam light to predict the trajectory of subsequent image beams that impinge on the remote surface. Also, the image beams and tracer beams that form the reflections of spot beams can be projected onto the remote surface/object in sweeping scans of one or more pseudo random patterns rather than a predefined pattern, such as an array or grid. In one or more embodiments, the trajectory of the spot beams can be observed so that a point of view of the reflections can be selected by, or automatically adjusted for, a user.
Additionally, in at least one or more embodiments, the light detector can also sense the reflections of visible/non-visible spot beams of light that form the reflections incident on the remote surface and/or objects. And the scanning light imaging device can employ the sensed reflections of this light to effect adjustments to subsequent spot beams scanned onto the remote surface and/or objects.
In one or more embodiments, the scanning light imaging device may be employed to pseudo randomly project beams of visible light onto the remote surface/objects and also pseudo randomly project other tracer beams of non-visible and/or visible light onto the same remote surface/objects. These pulses can be generated by modulating the output of light sources or shuttering the light detector of the reflected light pulses from the remote surfaces/objects.
In one or more embodiments, the light from the image beam and the tracer beam can be combined and projected onto the same location at the remote surface/object, or they may be projected onto two adjacent locations where the distance between the two locations is predetermined. The image beam light may have a wavelength in the visible spectrum, and it may also have a wavelength in the non-visible spectrum. If visible light is employed for tracer beams, the frequency of the light is typically so fast that the tracer beams are undetectable to the typical viewer. Also, if non-visible light is employed for the tracer beam pulses, the light wavelength may be in one or more non-visible spectrums, e.g., infrared, ultraviolet, or the like.
Furthermore, in at least one embodiment, the scanning light imaging device enables one or more safety interlocks between the device and the remote surface. For example, a determination is made as to whether or not the scanner is properly moving, and if not, the image beam and tracer beam are disabled until the scanner is properly moving again. Also, in at least one embodiment, if a excessively close object is detected between the device and the projection of the beams of light on the remote surface/object, the image beam and tracer beam may be disabled, or reduced in power until the moving object is no longer present between the device and the remote surface/object. Alternatively, the moving object may become the new remote surface/object that the scanning light imaging device pseudo randomly scans and senses the reflected beams light that are used to determine a new position for the new remote surface/object.
In at least one embodiment, the tracer beam non-visible light pulses are IR (Infra-Red) light that is projected by a scanner, such as an oscillating MEMS scanner, onto particular positions in a pseudorandom scanline trajectory that sweeps across the remote surface. A light detector, such as a camera, coupled with a processing unit, tracks the tracer beam light to obtain data for detecting N consecutive preceding positions of the pseudorandom scanline trajectory and estimating the subsequent consecutive M positions of the scanline trajectory with respect to a current position of the remote surface/object. In one or more embodiments, multiple component image beams of visible light, for example, RGB (Red-Green-Blue) colors, may be modulated, based on a corresponding M pixels of an image in a memory (memory image), and combined to create discrete combined image beam pulses. The combined image beam pulses are projected onto the remote surface/object at the subsequent estimated positions after the current combined image beam position. Furthermore, the reflections of the projected combined image beams incident on the remote surface/object, in addition to the tracer beam, may be optionally detected and compared with information previously stored in a memory. And based on that comparison, the subsequent estimated positions of the projected image beams can be adjusted on subsequent pseudorandom sweeps, progressively, to improve the projected image's sharpness, brightness, and color. The combined image beam may also include information about how a known reflected image of the remote surface/object is to be displayed to a user.
In one or more embodiments, analysis of reflections of pseudo random beam patterns traced out by fast sweeping laser beams, may be employed by robots and other computational entities to “make sense out of a world.” The image projection device and light detector may be employ the reflections of the pseudo random beams to quickly and efficiently perceive and recognize (“classify”) living moving things (humans, pets and other animate objects) that robotic systems need to account for to safely navigate and be useful beyond the confines of a safety cage in an automated assembly line.
In one or more embodiments, super resolution of illuminated physical dimensions and positions of remote surfaces and/or objects may be provided with a high speed sweeping and sharply focused laser beam “spot” and tracking the spot's reflections arriving at individual sequential binary pixels that asynchronously self-report in real-time, e.g., an array of binary pixels may also be referred to as a “twitchy pixel array” that is formed with an SPiM pixel array.
In one or more embodiments, a highly preferential signal discovery is provided by sorting true pixel events caused by the image beam's reflections on a twitchy pixel array, triggering a known characteristic sweep pattern, and differentiating these events from false pixel events e.g. caused by pixel dark noise” (e.g sensor noise caused by one or more of thermal random electrons and EM interference) and/or by stray, ambient or spurious photons impinging on the twitchy pixel.
In one or more embodiments, substantially high (super) levels of resolution may be provided by ultra-fast self-reporting binary (twitchy) pixels in an array, such as an SiPM pixel array, that may be used by a laser spot scanning device to observe when (accurate to the nanosecond) a first photon(s) of the scanning laser spot's reflection arrives at successive pixels in the array. For example, if the scan time across the pixel array is 100 microseconds (e.g. when scanning at 10,000 lines per second), and if the triggered pixel pixels along the trajectory are observed with 1 nanosecond precision ( 1/100th of the approximate time interval of 100 ns elapsed between successive triggered pixel events—the approx. time interval elapsed between avalanches caused by the scanning spot's reflections imaged on to the sensor) then an estimate may be determined for the true instantaneous position of the beam's spot on a remote surface, by interpolating the spot's position from the spatio-temporal trajectory observed as a series of events in the pixel array. In this way, the degree of super resolution can exceed by as much as 10 times the linear discrete resolution of the array.
In one or more embodiments, if 1000 columns of pixels span across a 50 degree angular field of view (FOV), then each column has 0.05 degree of view (view frustum 1/1000×50 degrees). Also, by tracking the time of arrival at individual pixels with nanosecond precision of the scanning spot reflections focused onto the sensor's pixel grid, then an estimate may be determined based at least in part on the beam's instantaneous position as a function of time to well beyond 0.005 degree angular resolution. Hence 10,000 positions or “10K” resolution, as 10,000×0.005 degrees equals the FOV's 50 degrees width.
For hundreds of millions of users using billions of computing devices, the availability of a physically small, low-power, high-quality, high reliability, high resolution scanned imaging system with few or no visual artifacts may provide a significant advantage. These advantages may be particularly significant for devices where both the physical size, the image rendering speed and latency and resolution of the imaging systems is critical, such as augmented reality head mounted displays (AR-HMDs). With a small, low-power, built-in pico projectors, such small computing devices can display information, effectively, in very high-resolution, without the physical size and high power consumption rate normally associated with a conventional pixelated and frame by frame rendering display systems.
Power efficiency is also very important, particularly for small personal devices, because of the limited battery life with daily use. Efficient projection of light with limited use of filters, polarizers, and the like, reduces overall power consumption, while providing a high quality display. The mixing of light falls into at least two general categories: additive mixing and subtractive mixing. In additive mixing, component light signals are combined with each other. In subtractive mixing, some light frequency components are filtered out, transmissively or reflectively, or subtracted from the original whole. Some of the conventional display technologies, such as LCD and DLP, use subtractive mixing as a basic part of their operation. Subtractive mixing of light beams is generally wasteful of energy because light (photons) is first generated and then partially blocked (subtracted), wasting the already generated light. Subtractive mixing is used to increase image brightness and enhance contrast between the brightest and darkest pixels. In display systems eventually utilized for displaying the image, resulting in poor overall efficiency.
Another important aspect of a display technology is reliability. With few moving parts, low power consumption, and low heat generation, reliability of invention may be generally greater compared to other display technologies having similar quality.
The feedback aspects, for both tracer pulses and image beam, of the invention enables uses in applications that are not possible, or are more difficult to realize, with other technologies to display images on remote surfaces and also detect multi-dimensional positions of remote surfaces and/or objects that may be stationary or moving. For example, the invention allows automatic adjustment of a display in real-time based on a perspective/position of the viewer/user. The user may move around a remote display screen while the invention automatically adjusts the displayed image to provide the appropriate perspective as viewed from each new position of the user with respect to the direction of projection onto the screen. This feature may have uses in immersive applications, such as video games. A variation of this capability is that the projected image may be displayed on an un-even surface of a screen, such as a textured wall, fabric, or other background with texture or curvatures that would otherwise distort the projected image. These features are more fully described below with respect to
Even though various embodiments refer to the RGB color space, other color spaces may also be used. For example, YIQ, YUV, YCbCr, and the like, color spaces may also be used to provide an image for projection. Similarly, more than three basic colors may be used. For example, in addition to the Red Green Blue color sources, other emissive spectral component color sources may be used, such as an Orange color source, for example, in the wavelength range of 597 to 622 nano-meters (nm), a Yellow color source, for example, in the wavelength range of 577 to 597 nm, or a Violet color source, for example, in the wavelength range of 380 to 455 nm. In this way, four or more component color sources may be used to project the image on a remote surface.
Generally, use of additional component colors may remove some tradeoffs, for example, the tradeoffs between efficiency, efficacy (characterized as perceived lumens per watt), gamut (broadest color range), and fidelity, characterized by avoidance of perceptive artifacts, such as spatial, temporal, motion, or color artifacts. Such tradeoffs may have to be made in both spatially rasterized and field-sequential color display systems, like LCDs, having addressable display elements or pixels. The use of a greater number of coherent monochrome sources, such as laser beams, reduce speckle that may be caused by self-interference in the reflected beam of each component light beam. The greater number of component light beams may reduce speckle because the component light beams are not coherent with respect to each other and may cancel out.
Multiple component light sources of substantially identical wavelength may also be used for added peak power, light efficiency, scanning, and detection speeds. For example, multiple semiconductor light sources, such as LEDs and laser diodes, may be optically combined to generate a brighter and more efficient light beam. Speckle may be reduced due to reduced phase coherency in such “gang source” systems where multiple near-identical wavelength component light sources are used.
Illustrative Operating Environment
Electronic displays for computing devices, such as workstations, desktop and laptop Personal Computers (PC), mobile devices like mobile phones, PDA's, and the like, as well as displays for entertainment-oriented devices, such as televisions (TV), DVD players, and the like, may be replaced or supplemented by scanning light imaging device (LID). In one embodiment, the LID is an integral part of the computing or entertainment device. In another embodiment, the LID may be a supplemental device used in addition to, or in place of, a conventional display and/or detecting positions of remote surfaces/objects for a vehicle navigation system or an augmented reality system.
One embodiment of a computing device usable with the LID is described in more detail below in conjunction with
Computing devices typically range widely in terms of capabilities and features. For example, a mobile phone may have a numeric keypad and a few lines of an LCD or OLED display on which a small amount of text and graphics may be displayed. In another example, a computing device may have a touch sensitive screen, a stylus, and a relatively large display in which both text and graphics may be displayed.
A computing device may include a browser application that is configured to send/receive and display web pages, web-based messages, or the like. The browser application may be configured to receive and display graphics, text, multimedia, or the like, employing virtually any web based language, including a wireless application protocol messages (WAP), or the like. In one embodiment, the browser application is enabled to employ Handheld Device Markup Language (HDML), Wireless Markup Language (WML), WMLScript, JavaScript, Standard Generalized Markup Language (SMGL), HyperText Markup Language (HTML), eXtensible Markup Language (XML), or the like, to display and send information.
Communication media used with computing devices typically may enable transmission of computer-readable instructions, data structures, program modules, or other types of content, virtually without limit. By way of example, communication media includes wired media such as twisted pair, coaxial cable, fiber optics, wave guides, and other wired media and wireless media such as acoustic, RF, infrared, and other wireless media.
The display of images and/or video data using the LID is different from the display of the same images/video on more conventional displays. Conventional displays generally are arranged with some form of pixel addressing in the display area. The pixel address may be specified by timing, as in raster scanners like CRTs using horizontal and vertical blanking signals (H-sync and V-sync, respectively), or by row-column address pairs like transistor/LED (Light Emitting Diode) arrays in LCDs. In conventional displays, the area of the display is generally quantized as a fixed grid with equal sized tiles or spatial quanta, also referred to as pixels. In such display systems, the illusion of motion is created by quantizing continuous time and space into discrete and equal time and space quanta, also referred to as frames. Generally, a fixed frame rate, expressed as Frames Per Second (FPS) is used to record and play back moving images. This quantization of time into frames, and image into pixels, introduce temporal and spatial artificial visual artifacts, respectively, during the display of moving images, such as jagged lines (spatial), aliasing (spatial and temporal), image blurring (temporal), judder (temporal), and the like, further described below.
These address-based pixel organizations are fundamentally different from the pseudo random scanning method used in an LID. The address-based displays generally require a defined frame format with specific and rigid timing requirements, as is well known to one skilled in the relevant arts. For example, in a raster scanner, scanned lines (scanlines) are displayed in consecutive order, as parallel horizontal lines, one after another from the top to the bottom of the screen. In contrast, the MEMS scanner for the LID can oscillate and project light in a pseudorandom pattern onto a remote surface, where the scanlines of an image beam and/or a tracer beam are primarily traced out in a direction based on the image or spot beam to be projected, without relying upon a particular spatial or temporal relationship with the previous or the next scanline.
Conventional scan patterns, in terms of both timing and spatial regularity, digital sampling, and quantization in general create a number of visual artifacts, such as jagged slant or diagonal lines, especially visible in low-resolution imaging systems, image blurring, motion blur (may occur because of a basic mismatch between continuous human vision and quantized digital imaging system), judder (defined as small unnatural jerky movements in motion pictures, either in space or in time. In space, judder can be the result of consecutive film frames not advanced precisely to the same position at the projector gate. In time, judder in video may be noticed because 24 frames per second for film source does not divide evenly into 60 fields or frames per second for NTSC video, and some film frames' content is shown on the screen for more time than other frames' content), moirés (pattern resulting from two grids that are superimposed over one another), screen door effects, aliasing, and the like. These artifacts results, in one way or another, from quantization and digital sampling.
However, since the LID is relatively analog in nature and in its operation as compared to conventional displays, does not depend on quantization, even though at some points through the process a LID implementation can process digital data. For example, reading an image from memory to display may involve some digital processing, however, once the image is ready for projection using LID, the process is largely analog, as more fully described herein.
Another difference between the LID and conventional displays is tracking and feedback.
Conventional displays are feed-forward in their basic operation, sending image data in one direction: from the source of the image, for example, memory or DVD, to the destination, which is the display device. Generally, no feedback is needed for basic operation and no data is read back from the conventional display. In some implementations of conventional display devices, the displayed image may be read back or sensed and compared with the source image to increase the quality of the displayed image. However, such feedback is for quality enhancement as opposed to being part of the basic operation of the conventional display devices. The display method used in LID may use feedback from the tracer beam, for example, IR pulses, to determine the next screen position on the scanline trajectory by trajectory prediction and/or estimation. Once the next screen position is so predicted, the memory image for the corresponding screen position is obtained and used to modulate the component image beams for combining and projecting onto the next screen position.
Because the scanlines can be pseudorandom in the LID, generally, the timing information (usually included in video frames) needed for display of a video stream on a conventional display device, may not be needed for display of the same video stream on the LID. In one embodiment, the active video signal, the sequence of images to be displayed, that is sent to a conventional display screen, may be stripped, in real-time, from the formatting information associated with the conventional displays, such as H-sync and V-sync signals and/or other timing information, for display using LID. In another embodiment, the active video or other image to be displayed using LID may be generated for LID or pre-stripped at the source of the video or image. In yet another embodiment, both of the above embodiments may be implemented by dynamically determining whether an image has display format information or is pre-stripped. In still another embodiment, the timing information included in video frames may be used to extract information that may be used to improve quality and/or perceived resolution. For example, a weighted average of multiple frames may be used to insert precise interpolated inter-frame pixel values that reduce unwanted visual artifacts.
Many graphics programs, such as video games and programs for 3-D (three Dimensional) manipulation of objects, may generate images with effective resolutions that are significantly beyond the resolutions that can be displayed by conventional display devices. Such high resolution graphics generated by these graphics programs may specially benefit from a projection system, such as the IPD, that is substantially free from quantization effects and has very high effective resolution.
Tracer beam 122 used for scanline trajectory prediction is also directed to scanner 110 and reflected to screen 114 or another remote surface/object. Detector 112 is used to detect the reflection of the tracer beam off screen 114 or another remote surface/object. Detector 112 sends timing to and screen position information [x, y] to processor 116 coupled with memory 118 holding an image to be displayed on screen 114 or reflected off another remote surface/object. Detector 112 can also be used to optionally detect the reflection of the image beam off screen 114 or another remote surface/object that may be stationary or moving. Additionally, in at least one embodiment, a separate detector 113 can be included to separately detect the reflection of the image beam off screen 114 or another remote surface/object. Furthermore, in one or more embodiments, information provided by detector 112 and separate detector 113 may be employed to triangulate one or more of a position of the other remote surface/object that is stationary or moving. Processor 116 is also coupled with light source driver 102 to control the modulation of component image beams, and generation of tracer beam 122 by tracer beam generator 106.
In one embodiment, component light sources 104 may include red, green and blue (RGB) color components. In another embodiment, component light sources 104 may include other color components such as orange, yellow and violet in addition to RGB. In one embodiment light sources 104 are LEDs (Light Emitting Diode), while in another embodiment, light sources 104 are lasers. In yet another embodiment, light sources 104 are laser diodes. Those skilled in the relevant arts will appreciate that many types of light sources may be used to generate component lights, such as red, green, and blue, and the like, without departing from the spirit of the disclosure.
Component light sources 104 produce component image light beams that are combined by a beam combiner 108 to produce a combined image beam. In one embodiment the beam combiner 108 is an optical device, such as a prism, dichroic mirrors, or the like. In another embodiment, the beam combiner 108 is an electronic device that may be used to convert light components into electrical signals, mix the electrical signals into a mixed signal, and convert the mixed signal back into a combined image beam. An electronic mixer may be used if intermediate processing of the light beam, such as digital or analog filtering or other control and processing, is desired.
In one embodiment, scanner 110 may be a MEMS device with a precision built mirror with at least a two-axis gimbal for independently controlled rotation about two orthogonal axis. In this embodiment, the mirror may sweep pseudo randomly scanlines that cover any screen position on the surface of screen 114 or another remote surface/object. In another embodiment, scanner 110 may be a mirror with other types of directional controls, such that a scanline may be projected on every screen position on screen 114 or another remote surface/object. For example, polar or cylindrical adjustments and corresponding controls may be used to point the mirror to direct the reflection of image beam to any screen position on screen 114 or another remote surface/object. Because of the rotation of the mirror, a scanline projected on screen 114 may have a slight curvature instead of being a straight line. Scanner 110 may work in a color sequential mode, where the image beam sequentially varies across multiple colors and the image is reconstructed by the viewer by virtue of time integration of the various color values observed.
In another embodiment, that may be useful for highly mobile images, such as movies, a multiple-color system may be implemented using multiple primary colors simultaneously. The primary colors may be separated out by using a prism, dichroic beam splitters or dichroic mirrors, or by using separate sub-pixels with color filters. In another embodiment, a full, broad-spectrum white source may be used for illumination, and the white beam may then be split into its color components which are separately observed by multiple lines in a linear array sensor.
A particular scanline projected by the scanner 110 onto the screen 114 is not aimed, in a feed-forward fashion, at any particular predetermined position (or curve, when referring to all points on the scanline) on the screen 114. Rather, the scanline is pseudo randomly projected at along some arbitrary trajectories, fast sequences of adjacent positions on the screen 114 and these trajectories and positions are observed and detected by a detector, more fully described below. This feedback arrangement is generally more precise and accurate than feed-forward, because the actual position of the projected scanline on the screen is determined, instead of a predicted feed-forward position, which may be off due to many causes, such as vibration of the scanner 110 and/or the screen 114 or another remote surface/object. Feedback inherently makes image correction on the screen possible, for example, to counter screen imperfections and/or vibrations, because feedback is after-the-fact observation of an event (e.g., scanline position on the screen), rather than before-the-fact prediction and/or specification of the event, as is the case in feed-forward systems. In one embodiment, screen 114 is a typical front projection screen with a high reflexive index. In another embodiment, screen 114 is a back projection screen with diffuse transmittance for passing light through. In this embodiment, the other components shown in
In one embodiment, detector 112 is a monochrome camera. The monochrome camera detects single colors, such as red, green, or blue. Monochrome cameras may also detect IR light. A monochrome camera may be useful when the tracer beam 122 is a visible pulsed light beam. In this embodiment, the light beam pulses are of short enough duration that would be imperceptible to the human eye. In another embodiment, detector 112 may be an IR detector used to detect pulses projected by the tracer beam 122. In yet another embodiment, detector 112 may be a CCD (Charge Coupled Device) or SiPM (Silicon Photo Multiplier) array. The CCD or SiPM array may be a single row CCD or SiPM array or it may be a two dimensional CCD or SiPM array.
In yet another embodiment, multiple single row CCD or SiPM arrays may be used. In this embodiment, a two-dimensional projected image is optically collapsed into two orthogonally related linear image components. Each of the two linear image components may be detected by a separate single row CCD or SiPM array. This way, a target object on the projected image may be detected and tracked. In the past, a camera system constructed from specially adapted optics and sensors—could be optimized to detect and track one or more target objects, for example, dots or small bright features, in a broad field of view. With simple mirror optics a single linear array sensor is sufficient to detect both location and signal intensity of the dots in a 2D field with a minimum of computation. Positional observations can be made at very high speed with an accuracy not attainable with conventional camera systems. However, the LID eliminates the trade-off between spatial resolution and shutter speed as observed in existing array sensors.
In still another embodiments, if a singular target object, for example, a single screen position the light level of which exceeds a pixel threshold of a detector array (for example, CCD or SiPM array), a folding optics arrangements may be used to superimpose a dimension Y (for example, vertical) of an image onto a dimension X (for example, horizontal) of the image so that information contained in both dimensions may be measured and detected by a single linear CCD or SiPM array. US Provisional Patent application, Ser. No. 61/002,402, referenced above and to which priority is claimed and incorporated by reference, discloses this arrangement. The folding optics arrangement may be implemented using a mirror, a half-mirror (for beam splitting), or a reflecting prism, among other options. In one embodiment, pixels in the detector 112 array may have the same associated threshold. In another embodiment, pixels in the detector 112 may have a different associated threshold based on certain criteria, for example, the contrast expected in the image that will be displayed. In yet another embodiment, the pixel thresholds may be set dynamically based on certain criteria, for example, the average darkness or brightness of the image about to be displayed. The dynamic setting of the pixel thresholds may be performed during a calibration cycle of detector 112, where the pixel threshold value is set to just below the brightest value observed in the detector sensor array.
The folding optics embodiment of detector 112 enables out-of-order reporting of screen positions exceeding the pixel threshold. Additionally, this embodiment enables dimensional superposition, as more fully described below. In one embodiment, each pixel in detector 112 array may be set to a threshold. The threshold is set above the natural noise level, for example, the dark current of the electronics implementing the detector pixels. The threshold may also be set at a higher level than the natural noise level, but below the expected brightness of the target object to be detected. This way, the brightest screen position in the projected image exceeds the pixel threshold and triggers detection of the surface position. Each pixel in the detector 112 array has a predetermined address (pixel address) typically corresponding to a sequential count that can either be hard-wired or assigned during initialization of the scanned imaging system.
When a pixel in detector 112 array exceeds the threshold value, a pixel “hit” event, the address of the pixel is reported, for example to processor 116 (see
In this embodiment, no electronic or mechanical shutter may be needed for detecting pixel hit events. The pixel thresholds and resetting together act as an effective shutter mechanism for detector 112 array. An effective shutter speed of a sensor (pixel) in detector 112 array is at most as slow as the reset time of any one pixel, typically on the order of a few micro seconds or less. The shutter speed for the detection of a pixel hit event, may generally be limited by the sensitivity of a pixel trigger circuit to detect a minimum amount of charge exceeding the preset threshold value (trigger). If the value to be detected is a sufficiently bright strobe, the detection would be nearly instantaneous. For example, an avalanche photo diode detector based pixel might require as few as 10 photons to detect a hit. When high speed beam detection is required, adjacent pixels in the detector corresponding to screen positions on the scanline, may be asynchronously (and typically time-sequentially) triggered, effectively causing the detector to have little or no shutter speed limit. Furthermore, nearly simultaneous observations of different pixel hit events may be pipelined for processing to calculate and predict the trajectory of the scanline. A precise reference clock may be used to time-stamp each pixel hit event observation for accurate trajectory calculations. Such a reference clock may provide GHz (Giga Hertz; nano-second time resolution) time-stamps.
The surface position, brightness, and timestamp associated with a pixel hit even may be obtained asynchronously. Therefore, the timing of the observed pixel hit events is independent of sampling speed, sampling intervals, or shutter speed of detector 112, thus, avoiding measurement errors and quantization effects, which typically result in image artifacts such as aliasing in traditional array sensors. Reducing quantization artifacts is an important architectural consideration. In the cases that the observed object has a known periodicity, clock accuracy and motion accuracy can be derived independently from the sensor spatial resolution, reducing motion blur. In one embodiment, the tracer beam 122 (see
In one embodiment, dimensional Superposition entails beam folding in addition to “deconstructing” the image, e.g., optically reducing the image dimensionally from a 2-D space, having an X- and a Y-dimension, into two or more 1-D spaces. In this embodiment an N×N image detector array may be reduced to a single N-pixel linear sensor array by “folding” and superimposing each of the two dimensions of the image onto one linear array. A 2-D image beam may be collapsed into two 1-D linear arrays using one or more cylindrical lenses that split the 2-D image beam. Beam folding may be performed by guiding the image light exiting from a cylindrical lenses onto a single linear array by optical means, for example, using mirror(s), prism(s), grating(s), or waveguide(s). In one embodiment, the single linear array may be a monochrome linear array. In another embodiment, the 2-D image may be split, resulting in two split image beams. One of the split beams may be rotated and recombined with the other split image beam, so that one cylindrical lens and corresponding sensor array may be needed.
In this embodiment, a single surface position where the IR pulse is projected on the surface, may result in two separate illuminated dots on the linear array. One dot represents X-dimension and the other dot represents the Y-dimension of the surface position on the original 2-D image. Thus, the bit values (representing, for example, brightness) and addresses of the two dots in the single linear array allow the spatial surface position in the 2-D image, as well as the intensity and color of the 2-D image corresponding to the surface position be reconstruction rapidly and efficiently, as two values have to be read from the same sensor in the single linear array. This embodiment allows the scanned laser imaging system to track a highly mobile bright objects in its Field of View (FoV) with N×N spatial resolution at a speed limited by the pulse width (or period) of the tracer beam. In this case, the effective resolution of the IPD is equivalent to speed x pulse period. In one embodiment, for accurate scanline trajectory calculations, multiple sequential readings can be made as described and the result can be hyper-resolved by interpolation for scanline sweep segments with known speed and smooth curvature. This way, the IPD's scanner may achieve high resolution and great color depth, using a single monochrome array sensor.
In one embodiment, improved spatial color accuracy, for example, hue and luminance, may be independently achieved, using the same set of optics and sensors. To detect the screen position accurately based on a reflection of incident beams projected on the screen 114, a narrow band frequency light source may be used, in the form of a narrowly collimated illumination beam that illuminates a very narrow spot, for example, an IR or UV beam. If all light beams have substantially the same frequency, the optics may be optimized or tuned for this frequency. A broad spectrum light source or a mix of multiple primary color components, representing the image to be displayed, may be superimposed and projected onto the screen position to determine the hue and luminance information of the reflected image beam. To enhance the sensitivity of the color measurements, and to allow for some blurring and color aberrations inherent in using the broad spectrum light in the optics of the detector 112, values of multiple pixels in the single linear array may be combined. This may be possible because due to the laser collimation accuracy, the image information may be generally centered on the same location as the narrow beam location, which has been already determined.
In one embodiment, both the screen position and visible image color components may be read simultaneously by subtracting IR pulse value of the screen position from sum of the adjoining “lit-up” screen positions. In another embodiment, the periodic IR pulse may be used to determine the precise scanline trajectory. The scanner may operate in color spatial field sequential fashion, where for each color, location is calculated by spatial interpolation based on the time-stamp associated with the screen position.
In one embodiment, processor 116 is a programmed microprocessor coupled to memory 118 containing the image to be displayed. As is well known to those skilled in the art, embedded programs running on the microprocessor may be used to perform appropriate signal processing using processor 116. In one embodiment, processor 116 is a digital signal processor (DSP) with specialized instructions for processing signal information. In another embodiment, processor 116 is a circuit for performing hardware-based processing and calculations. In yet another embodiment, processor 116 is a software component running on a microprocessor or microcontroller running other applications as well. Those skilled in the art would appreciate that processor 116 may be implemented using multiple processors, each processor performing a portion of the calculations needed.
In one embodiment, light source driver 102 is a circuit for modulating light sources 104 according to image control signals 124 output from the processor 116. Light source driver 102 may also process timing information is 126 to control tracer beam generator 106. In one embodiment, light source driver 102 modulates light sources 104 and controls tracer beam generator 106. In another embodiment, light source driver 102 may be implemented as two separate modules, one for controlling light sources 14 and one for controlling tracer beam generator 106.
Not all the components shown in
In operation, with continued reference to
Detector 112 determines the screen position as defined by a pulse from tracer beam 122. Processor 116 predicts the subsequent screen positions based on the previous screen positions on the same scanline. The subsequent screen positions are used to obtain image pixel information from memory 118 and display on the subsequent predicted screen positions. In one embodiment, the image pixel information from memory or another image source, such as a graphic engine, may correspond to one or more screen positions. The image to be displayed may be a described as a polygonal element or continuously interpolated color mapping. This process may be continuously repeated for pulse after pulse.
For each detected pulse, the corresponding surface position information is provided to processor 116 by detector 112. In one embodiment, the screen position information may include raw data as collected by detector 112, for example, an array index of detector 112. In this embodiment, the raw data may be further processed by processor 116 to calculate the [X, Y] coordinates of the detected beam of light. In another embodiment, the surface position information may include [X, Y] coordinates of the detected pulse, as determined by detector 112. Detector 112 may also provide time of detection, to, to processor 116. The time of transmission of the tracer beam from the tracer beam generator 106 to processor 116, the pulse “flight time,” may be calculated by subtracting the time of generation of the pulse from the time of detection of the pulse. The pulse flight time may be used to estimate the distance of the particular point on screen 114 where the pulse was detected to scanner 110. Knowing this distance enables processor 116 to adjust the brightness and modulation of the component image beams, and tracer beam pulse frequency to compensate for a rough or irregular surface of screen 114 or another remote surface/object that may be stationary or moving.
In one embodiment, successive screen positions traversed by the pseudorandom scanlines, used to project combined image beam 120 onto screen 114, are looked up by high speed processor 116 in a memory reference table and the color values of the image to be displayed corresponding to the screen positions are rendered on the screen positions nearly instantaneously. Hardware graphics processors can look up such color values and any related computations at multiples of GHz (Giga Hertz, a billion cycles/second) clock speeds. Thus, pixel color values, typically specified as 24, 32 or 48 bit color vectors, can be computed billions of times per second, with a latency of about a few nano seconds (billionths of a second). This rate of processing is more than sufficient to render the equivalent of 30 frames of two million pixels each second (60 million vectors per second). Thus, such computational speeds are more than sufficient for LID 100 to render HDTV (High Definition TV) quality video.
In one embodiment, the projection and detection functions described above may be alternated on a small time scale, for example, on the order of a few nano-seconds. In this embodiment, in a first phase, a projection cycle is performed projecting a portion of a scanline on the screen, while a detection cycle stands by. In a second phase, the detection cycle starts while the projection cycle stands by. The first and second phases may be performed on a single or a few screen positions. In another embodiment, the projection and detection functions may operate simultaneously. For example, two sliding windows overlapping in time may be used to simultaneously project and detect multiple screen positions. One sliding window may be used for projection of an image onto multiple screen positions, while the other sliding window may be used for detection of previously projected multiple screen positions.
In its basic operation as described above, LID 100 is independent of frames of video in contrast to conventional projectors or other display devices. In LID, pixels on the projected image are refreshed not by an orderly scan, such as raster scan, but by pseudorandom scanlines. As such, the limitations associated with quantization/digitization, frame rates, and the like, as described above, largely do not apply to LID 100. For example, HDTV needs to display about 180 million dots per second for 30 frames per second of 1920 columns, 980 rows for each frame, and three colors per pixel. As a result, every pixels must be re-drawn because of the regular frame rates. This type of “overkill” is necessary to suppress some of the quantization artifacts discussed above. In contrast, LID 100 can update a pixel using a single combined image beam 120 if the pixel is predicted to fall on the current scanline, avoiding the need to process/calculate pixels in regular sequence to get rid of artifacts.
Additionally, little or no calculations need be performed when there is a span of non-changing image value covering multiple screen positions or another remote surface/object positions. For example, for a solid background color the value of the image beam corresponding to screen positions falling within the solid background need be calculated once and used tens, hundreds, or thousands of times during one or more scanline sweeps. Human visual system is persistent in some respects, holding a perceived brightness or color value for a small span of time, on the order of a few microseconds. Additionally, the human visual system may integrate successive values of a pixel over time provided the refresh rate is beyond human visual perception. The result of such integration may be a perceived as a color different from all of the successively integrated values of the pixel over time. There is no concept of frame involved in the LID, even though a sequence of image frames may also be displayed using the LID like any sequence of images.
In one embodiment, the expected reflection of the image on the screen or another remote surface/object at a particular position may be compared to the actual reflection value (for example, returned color intensity of each color of the projection beam colors). A difference between an expected beam reflection value at each position and the actual reflection value at the same position is an indication of the reflection/absorption response of the screen or another remote surface/object. Thus, images prior to projection may be observed and acted upon during and after pseudo random scanning.
In one embodiment, the difference between the expected and the actual reflection values may be used when on-screen, location-specific references are required that allow the LID to align and match its projection with great color and spatial accuracy to a predetermined location, color, or pattern. Thus, the projected image might complement, or alternatively mask, a reflected image. For example, a screen artifact, such as a user-interface component embedded in the screen, like a microphone or a camera lens, or a non-uniform screen area may be detected. Based on such detection, the LID may adjust the projected image to avoid projecting the image on such screen artifacts. This feature may be useful in a video conferencing session, where the projected image of a first party in the conference needs to be properly aligned with the camera aperture embedded in the screen (which may be considered as a small irregularity in the screen surface) so that an observing second party to the video conferencing session looks directly at where the first party is looking, that is, straight into his/her eyes. If this embodiment is implemented on both sides in the video conference, the gazes and observed facial perspectives of both parties may be properly and mutually aligned. This feature enables a life-like and natural eye-to-eye contact, greatly facilitating communication between humans. In addition, due to the ability of the scanner to detect the lens aperture accurately, the sweeping projection beam can be spatially masked and can be synchronized with the shutter interval of the camera so that the camera is not blinded by the projected image.
In another embodiment, the projected image may be aligned with the projection surface, for example, in a situation where the projection surface is in motion with respect to the projector or the viewer, and the projected image needs to be angularly and/or spatially adjusted, for example, by rotation, translation, and/or scaling, to match the moving projection surface. The LID may have high scanline projection speeds, for example about 10,000 feet per second (fps). At high projection speeds, such image adjustments may be made faster than the human eye can detect. In this embodiment, the RSPT may create an image that seems physically attached to the moving projection surface. One application of this embodiment might be the projection of advertising on moving vehicles or objects. Another application that may require precise control is an electronic dashboard display where it is desirable to align the projected image accurately with the moving/vibrating control surface, particularly if that surface has an active (for example, emissive or reflective) display that needs to be complemented by the projected image. For example, in traffic control or mission control, projecting real time flight or vehicular information on a terrain map may be possible using this embodiment.
In yet another embodiment, a white board or other collaborative surface may be used as a screen for the LID, where written, printed, or projected images may be annotated with real, for example, erasable markers. The annotations or other markings may be superimposed on a known image that is projected onto the white board. Such markings may then be scanned in by the LID, so the markings can be added in real-time to the image or document being projected onto the collaborative surface, and/or stored for later use or further modification. In one embodiment, the detector in LID, for example detector 112 (see
This embodiment may be particularly useful in cases where the modifications on a real white board need to be available in real-time in multiple locations in a collaborative setting. During a collaboration session, an image, such as a system diagram, may be projected on a regular white board at multiple locations using the LID. Any modifications made to the projected diagram at any one of the locations participating in the collaboration session may be seen at all participating locations. In another embodiment, the LID may be a rear projection system. In this embodiment, when using a “dry erase” marker on a translucent screen, the LID may detect, from behind the screen, the ink left by the “dry erase” marker. In another embodiment, a physical object, for example, a pointing device, such as a stick or a finger, may be detected by the LID and used to augment the projected image. For example, if a participant at one location uses a stick to point to a feature on the projected image, other participants at other locations will see an augmented image including the pointer pointing to the same feature on the image. Similarly, in an immersive video game or a virtual reality (VR) environment, or Mixed Reality (MR) environment, physical objects, such as chairs, tables, avatars, player characters, and the like may be integrated into the scene, adding to the realism by making the VR experience more consistent with reality.
Those skilled in the art will appreciate that the same functionalities described above for LID 100 may be implemented using other arrangements of components without departing from the spirit of the present disclosures. For example, although LID 100 is shown and discussed with respect to a front projection arrangement, where the projected image is viewed by a user as reflected off screen 114, substantially the same concepts, components, and methods may be used for a rear projection arrangement, where the projected image is viewed on the other side of screen 114 via light transmission.
Illustrative Computing Device Environment
As shown in the figure, computing device 200 includes a processing unit (CPU) 222 in communication with a mass memory 230 via a bus 224. Computing device 200 also includes a power supply 226, one or more network interfaces 250, an audio interface 252 that may be configured to receive an audio input as well as to provide an audio output, a display 254, a keypad 256, a light source driver interface 258, a video interface 259, an input/output interface 260, a detector interface 262, and a global positioning systems (GPS) receiver 264. Power supply 226 provides power to computing device 200. A rechargeable or non-rechargeable battery may be used to provide power. The power may also be provided by an external power source, such as an AC adapter or a powered docking cradle that supplements and/or recharges a battery. In one embodiment, CPU 222 may be used as high performance processor 116 for processing feedback and timing information of LID 100, as described above with respect to
Network interface 250 includes circuitry for coupling computing device 200 to one or more networks, and is constructed for use with one or more communication protocols and technologies including, but not limited to, global system for mobile communication (GSM), code division multiple access (CDMA), time division multiple access (TDMA), user datagram protocol (UDP), transmission control protocol/Internet protocol (TCP/IP), SMS, general packet radio service (GPRS), WAP, ultra wide band (UWB), IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMax), SIP/RTP, Bluetooth, Wi-Fi, Zigbee, UMTS, HSDPA, WCDMA, WEDGE, or any of a variety of other wired and/or wireless communication protocols. Network interface 250 is sometimes known as a transceiver, transceiving device, or network interface card (NIC).
Audio interface 252 is arranged to produce and receive audio signals such as the sound of a human voice. For example, audio interface 252 may be coupled to a speaker and microphone (not shown) to enable telecommunication with others and/or generate an audio acknowledgement for some action.
Display 254 may be a CRT, a liquid crystal display (LCD), gas plasma, light emitting diode (LED), or any other type of display used with a computing device. Display 254 may also include a touch sensitive screen arranged to receive input from an object such as a stylus or a digit from a human hand. LID 100 may replace display 254 or work in conjunction with display 254. For example, if display 254 is an output or write-only device, that is, an output device that displays information but does not take input from the user, then LID 100 may replace display 254. However, if display 254 is an input/output device or read/write device, then LID 100 may work in conjunction with display 254. LID 100 may display the output information while display 254 may take user input, for example, as a touch-screen display. This way, a user can view high quality output using LID 100 while inputting information via the touch-screen display 254, which may additionally output the same information viewed on LID 100. In another embodiment, described more fully below with respect to
Keypad 256 may comprise any input device arranged to receive input from a user. For example, keypad 256 may include a push button numeric dial, or a keyboard. Keypad 256 may also include command buttons that are associated with selecting and sending images.
In one embodiment, a light source driver interface 258 may provide signal interface with the light source driver 102. Light source driver interface 258 may be used to provide modulation and timing control information to light source driver 102. For example, if CPU 222 is used as processor 116 for processing feedback and timing information of LID 100, then light source driver interface 258 may be used to deliver image control 124 and timing information 126 to light source driver 102.
Video interface 259 may generally be used for providing signals of a particular type and/or formatting images for display on a particular type of display device 254. For example, if display 254 is a raster type device, such as a CRT, then video interface 259 provides the appropriate signal timing, voltage levels, H-sync, V-sync, and the like to enable the image to be displayed on display 254. If display 254 is LID, the video interface 259 may implement some or all of the components shown in
Computing device 200 may also include input/output interface 260 for communicating with external devices, such as a headset, or other input or output devices not shown in
In one embodiment, detector interface 262 may be used to collect timing and screen, remote surface/object position information from detector 112 and passing such information on to processor 116 and/or CPU 222 for further processing. In another embodiment, detector interface 262 may be integrated with video interface to 259 as one unit. In yet another embodiment, detector interface 262 may be external to computing device 200 and be part of an integrated external LID unit.
GPS transceiver 264 can determine the physical coordinates of computing device 200 on the surface of the Earth, which typically outputs a location as latitude and longitude values. GPS transceiver 264 can also employ other geo-positioning mechanisms, including, but not limited to, triangulation, assisted GPS (AGPS), E-OTD, CI, SAI, ETA, BSS or the like, to further determine the physical location of computing device 200 on the surface of the Earth. It is understood that under different conditions, GPS transceiver 264 can determine a physical location within millimeters for computing device 200; and in other cases, the determined physical location may be less precise, such as within a meter or significantly greater distances. In one embodiment, however, mobile device may through other components, provide other information that may be employed to determine a physical location of the device, including for example, a MAC address, IP address, or the like.
Mass memory 230 includes a RAM 232, a ROM 234, and other storage means. Mass memory 230 illustrates another example of computer storage media for storage of information such as computer readable instructions, data structures, program modules or other data. Mass memory 230 stores a basic input/output system (“BIOS”) 240 for controlling low-level operation of computing device 200. The mass memory also stores an operating system 241 for controlling the operation of computing device 200. It will be appreciated that this component may include a general purpose operating system such as a version of UNIX, or LINUX™, or a specialized computing communication operating system such as Windows Mobile™, or the Symbian® operating system. The operating system may include, or interface with a Java virtual machine module that enables control of hardware components and/or operating system operations via Java application programs. In one embodiment, mass memory 232 may be used as memory 118, for holding an image to be displayed using LID 100, coupled with processor 116 and/or CPU 222.
Memory 230 may further include one or more data storage 244, which can be utilized by computing device 200 to store, among other things, applications 242 and/or other data. For example, data storage 244 may also be employed to store information that describes various capabilities of computing device 200, a device identifier, and the like. The information may then be provided to another device based on any of a variety of events, including being sent as part of a header during a communication, sent upon request, or the like.
Applications 242 may include computer executable instructions which, when executed by computing device 200, transmit, receive, and/or otherwise process messages (e.g., SMS, MMS, IMS, IM, email, and/or other messages), audio, video, and enable telecommunication with another user of another computing device. Other examples of application programs include calendars, browsers, email clients, IM applications, VOIP applications, contact managers, task managers, database programs, word processing programs, security applications, spreadsheet programs, games, search programs, and so forth. Applications 242 may further include image processor 243, beam trajectory processor 245, and detector processor 247.
In one embodiment, image processor 243 is a software component that may perform functions associated with processing digital images for display using LID 100. For example, image processor 243 may used to fetch an image to display using LID 100 from memory 118. In one embodiment, image processor 243 works in collaboration with other components, such as video interface 259, detector interface 262, beam trajectory processor 245, and detector processor 247. Additionally, image processor 243 may be used to perform digital image processing operations on the image fetched from memory 118. For example, image processor 243 may use an adjustment coefficients matrix to adjust each color component of each image pixel of the image in memory 118 before using LID 100 to display the image. In one embodiment multiple adjustment coefficients matrices may be used to adjust different image parameters. For example, one matrix may be used to adjust brightness, while another matrix may be used to adjust saturation when using HSB color space. In one embodiment, RGB color representation may be converted to HSB, be adjusted according to the appropriate coefficient matrices, and converted back to RGB for modulation.
Those skilled in the art will appreciate that there are many image processing operations that may be performed on an image before displaying the image. For example, various filtering operations may be performed on the image to filter out noise, sharpen edges, and improve contrast. Such image processing operations may be based on the timing of tracer beam 122 pulses, the detected view angle of a viewer, the texture of screen 114, and the like.
Beam Trajectory Processor (BTP) 245 is used to process information about the pseudo-random scanline trajectory based on tracer beam pulses 122. BTP 245 may work in cooperation with image processor 243 to estimate the next screen position for projecting the image. In one embodiment, BTP 245 collect data about N successive tracer beam 122 pulses from a current scanline being scanned by scanner 110. Next, BTP 245 uses the N successive pulses to estimate the next M display screen positions on the current scanline. For example, BTP 245 may use numerical methods to fit a curve through the [X, Y] positions of the N successive pulses and estimate/predict the next M display screen positions on the current scanline. Those skilled in the relevant arts will appreciate that there are many numerical methods that may be used for this application. For example, least squares curve fit may be used to minimize curve fit errors. Subsequently, image processor 243 fetches image pixels from memory at 118, corresponding to the M display positions on the current scanline.
In one embodiment, the screen position estimation/prediction process described above may be repeated for each tracer beam 122 pulse that is detected by detector 112. In effect, a sliding window type algorithm may be used to continuously and accurately estimate and update the predicted position of the next screen position before the scanline actually crosses the predicted screen position. In this embodiment, the width of the sliding window is the N screen positions.
In one embodiment, detector processor 247 may work in collaboration with detector interface 262 to collect and preprocess data for tracer beam 122 pulses before providing such data to BTP 245 for trajectory estimations. Those skilled in the relevant arts will appreciate that image processor 243, BTP 245, and detector processor 247 may be integrated into one component. Similarly, the functions performed by each of these components may be decomposed and distributed over other components, software or hardware, of computing device 200.
Those skilled in the relevant arts will appreciate that some of the components described above with respect to
Generalized System Operation
In one embodiment, timing control component 304 is implemented as part of BTP 245 and/or a detector processor 247. In another embodiment, timing control component 304 is implemented as a separate hardware circuit that may interface with detector interface 262. Similarly, in one embodiment, intensity control component 302 may be implemented as part of image processor 243. In another embodiment, intensity control component 302 may be implemented as an independent component that is coupled with image processor 243.
In one embodiment, timing control component 304 takes as input timing information to from to detector 112 and outputs tracer beam 122 timing information, such as ts with pulse period T between pulses 306. Tracer beam 122 timing information may subsequently be used for generating tracer beam 122 via tracer beam generator 106. Timing control component 304 may also calculate pulse flight time by subtracting ts from t0. Pulse flight information may be used to calculate the distance of screen 114 from scanner 110, based on which image intensity may be controlled. Timing control 304 may also be used to vary pulse period T and thus, vary the effective resolution of the image projected using LID 100 dynamically. Dynamic, localized, real-time variation of image resolution may be useful to adjust the displayed image on an uneven surface of screen 114. For example, if the surface of screen 114 has an edge with a sharp drop or angle, such as a wall corner with a large drop, at a given resolution, a display pixel may fall partly on the top side of the edge and partly on the bottom side of the edge, thus, splitting and distorting the displayed pixel. However, if the displayed pixel is split into two pixels by increasing local resolution dynamically, then instead of splitting the pixel over the edge, one pixel at appropriate intensity is projected on the top side of the edge and another pixel and at another appropriate intensity is projected on the bottom side of the edge.
In one embodiment, dynamic resolution adjustment in conjunction with other features of LID, such as feedback and flight time information, may be used to project an image on several odd-shaped or angled walls surrounding the LID for creating a visually immersive environment. Such visually immersive environment may be used in video games where the player is at the center of the room in a virtual game environment. In one embodiment, a single LID may be used to project an image about 180° wide. In another embodiment, more than one LID may be used to project an image about 360° wide (for example, planetarium style projection), completely surrounding a viewer.
Another application of dynamic resolution control is focusing high resolution, and thus, high quality, where high resolution is needed most. For example, an image having details of a face against a blue sky background can benefit from the high resolution for showing facial wrinkles, hair, shadows, and the like, while the blue sky background can be displayed at a relatively lower resolution without sacrificing quality significantly or noticeably.
In one embodiment, intensity control component 302 determines intensity of component image beams based on pixel values of the image in memory 118 corresponding to the next M screen positions on the current scanline. The intensity of each component image beam for each predicted screen position may be further adjusted by adjustment coefficients in an image processing matrix. In one embodiment, detector 112 includes a color camera that detects combined image beam 120 from screen 114, in addition to detecting tracer beam 122, as another feedback signal. Detected combined image beam 120 may be used to further adjust displayed image quality by comparing detected combined image beam 120 at each screen position with the corresponding image pixel in memory 118.
In one embodiment, the adjustment of the displayed image at each surface position may be done over successive scan cycles, each scan cycle sweeping a new pseudorandom scanline, of the same surface position. As scanner 110 randomly projects scanlines onto screen 114, eventually each screen position is scanned again in a later scan cycle, providing the opportunity to further adjust the color and intensity of the projected image at each surface position, or add additional detail, possibly filling in small spaces missed in the previous scan cycles, to sharpen or soften edges as needed. Due to the high scan rate of scanner 110, each display pixel is likely scanned and adjusted multiple times at a rate that is imperceptible to a human viewer. The human visual system integrates successive adjustments of color and intensity into a perceived whole by averaging the color and intensity over time if such adjustments occur fast enough for the human visual system. Thus, even if in one scan cycle, the color and intensity of a display pixel is less than perfect as compared with the corresponding pixel of the image in memory 118, for example, due to lighting and/or screen 114 surface imperfections, the color and intensity of the display pixel is adjusted in the next few scan cycles and integrated by human eye before the human vision has a chance to perceive the imperfection in one cycle.
As an illustrative example, consider an image 406 of a face that is displayed using LID 402 on screen 114. Each screen position 408 on the face 406 may fall on one or more scanlines. When screen position 408 is predicted to be the next display position on a current scanline, processor 116 (or equivalently, image processor 243 shown in
For relatively large spans of uniform image portions on a pixel scale, for example, a portion of blue sky or white wall, the modulation of component image beams need not change because the same color and intensities are repeated for many contiguous pixels. A Run-Length-Limited (RLL) image coding and/or display algorithm may be used to reduce the amount of processing needed to display such images. Most graphical images, such as various pictures like sceneries, clothing, faces, and the like, have large spans of uniform image colors and intensities at pixel level and can benefit from RLL based processing to increase efficiency. Even larger spans of uniformity may be encountered in synthetic game scenes and software application graphics such as desktop business applications, web pages, and the like.
In one or more embodiments, the tracer beam projects a pattern on a remote surface or object (e.g a walking person or a moving vehicle), following sequentially arced patterns, preferable as “pseudo random” scan pattern of fast linear strokes, as in
In one or more embodiment, tracer beam 514 may be continuously emitted at a short wavelength of 405 nanometers that may be blue/Ultra-violet in color. However, due to the high speeds at which tracer beam 514 is scanned, the limited luminosity (luminous efficacy) of the short wavelength blue light may be less than 1 milliLumen and thus imperceptible to the vision of most humans.
A reflection 516 of tracer beam 514 is detected by detector 112 which is generally positioned in close proximity to light sources and optics 508, for example, next to scanner 110 (not shown in
In one or more embodiments, detector 112 provides feedback information, such as timing information to of a pulse 414 (see
Feedback control 502 provides control information 506 to light sources and optics component 508. Such control information include timing information ts, and modulation control information 308 (see
In one embodiment, with reference to
For instance, in one or more embodiments, if LID 402 is projecting an image of a car viewed from front when user 604 is viewing screen 114 from a vantage point along the direction of projection, then user 604 sees a front view of the car. Now, if user 604 moves to position-1 to the right of LID 402, then LID 402 calculates the new viewing angle for position-1 and projects the right-side perspective of the car image for user 604. Similarly, if user 604 moves to position-2 to the left of LID 402, then LID 402 calculates the new viewing angle for position-2 and projects the left-side perspective of the car image for user 604. Additionally, in one or more embodiments, a three or even six degrees of freedom position for detector 602 may be almost instantaneously determined for each pseudo random sweeping scan with one or more of photogrammetry or multi view stereo metric estimation methods. Further, this position determination may be employed as a low latency simultaneous localization and mapping method, which may be employed to project augmentations or attach labels onto real objects, such as the human fingers shown in
As described for
In one or more embodiments, substantially continuous scanning beam(s) moving in pseudo-random tracer pattern on remote three dimensional surfaces (objects, surfaces or screens) are tracked by one or more asynchronous sensors (e.g., twitchy pixels in linear or two dimensional SiPM arrays, with columns and rows address labelled to detect avalanche events emitted within less than a nano second, of light arriving at each successive pixel).
In one embodiment, the feedback and image adjustment mechanisms of LID may be used in an interactive virtual and/or augmented reality (VAR) system for interaction with user 604. In this embodiment, when user 604 approaches a projected object on the screen, the LID may provide many VAR capabilities, such as “zooming in,” revealing ever greater detail about the projected object from the correct perspective, “zooming out,” “panning left/right,” “panning up/down,” handling a projected object, for example, lifting or pushing, and most other interactions that may be performed on a real object. Furthermore, since few or no physical constraints exist in a VAR system, some interactions that cannot be performed with a physical object may be performed on a projected object. For example, user 604 may walk through a wall without breaking the wall, as light passing through glass. A “zoom factor” may determine the rate of magnification as a function of the distance between user 604 and the projected object. User 604 may approach any object in view on the screen. The zoom factor may depend on the relative distance and desired realism in the VAR system. These features may create enhanced depth & motion experience. Additionally, the scanned tracer patterns allow generation of a relatively exact instantaneous perspective of a remote surface or object in six degrees of freedom (framelessly and without unnecessary delays or eliminating a host of artifacts introduced by discrete quantizations).
In one embodiment, the LID renders a scene by continuous real-time adjustments of the projected image by referencing the image as viewed through a position camera aligned with the viewer's perspective, as described above with respect to
The position feedback and independence of quantization enables the LID to render objects in great detail, relatively unconstrained by any fixed resolution. The SiPM type pixels enable observation to be performed precisely in fractions of a nanosecond. In contrast, quantization employs frames that are snapshots, taken over 10 milliseconds (100 fps e.g.). The frames and their corresponding pixels are relatively coarse dimensional reductive lossy quantizations (forcing reality, best described in REAL numbers) into integer values. However, twitchy pixel arrays that employ t SiPMs can measure time in a 10 millionth fraction of the 10 millisecond frame interval, thus using this 10 million times more accurate time measurement to estimate the three dimensional spatial position of an edge of moving objects, such as fingers, pedestrians, or vehicles.
By concentrating the graphics subsystem computational resources, such as memory and processing power, on the rendering of graphics polygons describing the projected object, more detailed objects may be rendered. The system resources are more efficiently used because the field of view may be rendered with greater detail than a peripheral field, while still a sufficiently realistic peripheral vision experience is maintained. The peripheral field may be rendered in less detail, or with greater latency (for example, due to a lower processing priority), conserving computational resources such as memory and computing bandwidth. As discussed above, the distance of the viewer/user to the projected surface may be determined by detecting the tracer beam and determining the flight time of the tracer beam pulses. A total viewer distance, DT to an object is the sum of a real distance, DR, and an imaginary distance, DI:DT=DR+DI. DR is the distance from the viewer (for example, the viewer's eyes) to the position on the screen where the object is projected. DI is the distance of the object away from and behind the plane represented by the projection surface (for example, screen), measured along the direction of view. For example, in a video game or VAR environment, a game engine may control DI by the varying size, shading, and rendering of perceivable details appropriately. DT, may also be referred to as a radial distance (total perceived distance), that is the distance from the object in view to the viewer's eye measured radially, that is, along the direction of view. In addition to this radial distance, a correct angular perspective may also be determined, as discussed above.
Objects that can be rendered and viewed in different directions and angular positions may be limited by the screen geometry and the position of the viewer. In case of a standard single rectangular projection surface (for example, normal front or rear projection system configurations) the limiting factors are screen height and width, and the viewing distance. If projection is done on walls surrounding the viewer, little or no geometric limitations may exist for the field of view of the user and interactions with objects projected onto the screen. Apart from screen limitations imposed by geometry or physical configuration, the viewer, equipped with the position camera, may move freely about the screen and approach any object in his field of view, which is usually a limited subset of, a “view cone,” within the total possible field of view. When the viewer approaches the screen the objects in his view will tend to naturally increase in size because the viewer is getting closer to them. As the image on the screen gets bigger, the image also occupies a greater portion of the field of view of the viewer. Accordingly, the viewer expects to see more details about the object, just as in real world.
At this point certain problems may occur that are best illustrated with an example. In an illustrative example, the viewer is looking at a static outdoor scene including a mountain about 10 miles away, some trees, and some rocks. Without any image adjustments by LID, as the viewer moves closer to the screen, the distance of the viewer to an object, for example, a tree, is reduced exactly proportionally to the real distance traversed by the viewer towards the screen. Thus as the viewer approaches a far away object, for example, the mountain 10 mile away in the view, the mountain will appear to come much closer than it should. For example, if the viewer travels three feet, half the distance of six feet from his original position to the screen, he will see the mountain twice as close even though he has not actually traveled five miles (half the perceived distance to the mountain). Even though this change in perceived distance is an expected artifact in a static image, it immediately tells the viewer's brain that the mountain is actually just a number of pixels projected on a flat surface six feet away, and not a real mountain 10 miles away. Thus, as the viewer comes closer to the screen, his natural depth perception is violated by every object in the scene, except possibly those objects that are perceived as close to the screen in the foreground.
Additionally, without image adjustment, all objects in the projected view may have unaltered geometric positions fixed to the projection surface, which is clearly not what would happen in reality. Furthermore, in the far background, the horizon does not recede, as it does in the real world, but comes 50% closer as the viewer moves three feet. In real world, as the user walks towards a mountain in the distance and approaches closer objects, the angular positions of objects with respect to the viewer's field of view generally increase for all objects in the view, more for closer objects, and less for farther objects.
Furthermore, without image adjustment, details that were hard to see at some distance, for example a tree that was 15 feet away, are still hard to see, when the viewer gets three feet closer. So, getting closer has less effect than expected. Also, as the viewer gets closer to the screen, serious projection and display limitations become visible due to an excessively coarse image rendering granularity and pixel pitch and other quantization artifacts that destroy the “suspension of disbelief”.
The above visual faults may be more acute in a VAR environment. The visual faults that result from lack of proper adjustment to the projected image when the viewer moves with respect to the screen result in the loss of the carefully constructed illusion, which so critical to a full immersive experience.
The LID provides the capability to properly adjust the projected images, static, dynamic, or interactive, like VAR and video game environments, with respect to the viewer's position and field of view, to provide a realistic visual experience. Continuing with the illustrative example above, the viewer standing six feet away from the screen, may see in the center of the field of view a far away object, for example, the mountain. As the viewer moves half the distance to the screen—three feet—the system detects the viewer's motion and adjusts the screen size of the mountain correctly to half size, canceling the effect of the viewer moving 50% closer to the screen. The mountain is seen by the viewer as unaltered, as he would also see in real world, since the mountain is still approximately 10 miles away (less three feet) but the image is viewed from half the original distance to the screen. Without detecting the viewer's position, the mountain's apparent size would have doubled, as discussed above.
At the same time, a small bush in the foreground is left unaltered by the LID since the viewer's motion in fact results in the real distance to that bush being halved and the unaltered projected image should look twice as big, at half the distance, precisely as it would if it were a real bush. Additionally, since the bush is now quite close, a system using the LID, for example the VAR system, allocates some extra graphics resources to render more visible details in each leaf of the bush, and the like, to render a closer view of the bush, since the user is now closer and expects to see more detail. This is made possible by the dynamic resolution control feature of the LID. Possibly, as the viewer gets very close, the system may actually project a shadow of the viewer over the bush. Such rendering would further enhance the realism experienced by the viewer. The realism is further supported by the LID due to substantial lack of fixed pixel size, pixel position, pixel orientation, or scan patterns. The LID may render and display all objects in view in the natural looking detail with few or no obvious visual artifacts. An important point to note is that the LID is independent of a game controller, buttons, or keys to adjust the image. The LID may adjust the image automatically based on the position camera and the field of view of the viewer.
The stretching effect is caused by geometric projection of a line segment onto a plane having an angle α with respect to the line segment. The length of the projected line segment, Lp=L/Cos α, where L is the length of the line segment. In this case, Lp>L, causing the stretching of the line segment. Similarly, any other shape projected on a tilted screen is also stretched by the same factor of 1/Cos α. The same adjustments done for tilted screen 640 may be applied to a projection surface with small surface irregularities and/or angles, such as a fabric with wrinkles or angled walls, in a piece-wise fashion. This ability of LID to use the tracer beam feedback and automatically adjust the projected image in real-time enables projection of images onto uneven and irregular surfaces with substantially reduced or eliminated distortions.
At block 886, the tracer beam is detected. Various detection schemes may be used that detect the screen position of each pulse on the pseudorandom scanline, such as 2-D CCD arrays, beam-folding optical detectors, and the like. Several screen positions corresponding to the tracer beam pulses are detected. In one embodiment, a sliding window with a width of N screen positions may be used to detect the tracer beam. The N screen positions may subsequently be used to predict the trajectory of the scanline. The process proceeds to block 888.
At block 888, a portion of the scanline trajectory that is not yet projected by the LID is predicted based on the N screen positions detected at block 886. For example, a curve fit algorithm may be used to extrapolate and determine the next M screen positions on the scanline. The process proceeds onto block 890.
At block 890, stored image pixels or generated graphics corresponding to the next M screen positions are obtained from an image source, such as from memory coupled with the LID. The correspondence of image pixels with the next M screen positions are not necessarily one-to-one. For example, one image pixel may cover and correspond to multiple screen positions, depending on the resolution of the image to be displayed. The obtained image is then projected by the LID onto one or more of the M screen positions. In one embodiment, the next M screen positions are determined on a continuous basis, for example, using another sliding window with a width of M. The process terminates at block 892. Additional process details are described below with respect to
At block 810, detector 112 is used to detect tracer beam 122 pulses, and provide the raw data and/or preprocessed data associated with the pulses to processor 116. In one embodiment, a sliding window algorithm is utilized to collected data about the N preceding pulses corresponding with the N preceding screen positions. The process proceeds to block 815.
At block 815, processor 116 calculates the trajectory of the current scan line to predict and/or estimate the next screen position on the current scanline for display of image pixel from memory 118. In one embodiment, next M screen positions are predicted based on the N preceding tracer beam 122 pulses on the current scanline. In one embodiment, the determination/prediction of the next M screen positions is repeated for each of the M pixels as the current scanline sweep continues by the scanner 110, thus implementing a sliding window algorithm both at the feedback end where data are collected about N preceding pulses and at the prediction end where M next screen positions are predicted. The sliding window at the feedback end is N pulses wide while the sliding window at the prediction end is M pixels wide. The process moves on to decision block 820.
At decision block 820, the process determines whether adjustment coefficients are updated and whether pixel color values, such as intensity or saturation, need adjustment before display. If so, the process proceeds to block 825 where the pixel values obtained from memory 118 are adjusted using the adjustment coefficients before proceeding to block 830. Otherwise, the process proceeds directly to block 830.
At block 830, the next M screen positions on the current scanline are determined. As noted above, in one embodiment, the next M screen positions are predicted based on dual sliding windows, one at the feedback end where data about preceding N screen positions are collected, and one at the prediction end where each of the next M screen positions are determined based on the data collected about the preceding N screen positions. The process proceeds to block 835.
At block 835, component image beams outputted by light sources 104 are modulated according to the corresponding values of color components of the pixels of image in memory 118, where the pixels correspond to the next screen position on the current scanline predicted at block 830. For example, the intensity of the R (Red) component image beam may be set to the red component value of the image in memory 118 for the pixel to be displayed next on the current scanline. The process proceeds to block 840.
At block 840, the component image beams, for example, RGB components, are combined together to form one combined image beam 120. In one embodiment, a prism may be used to combine the component image beam. In other embodiments other methods currently known in the art or methods to be discovered in the future may be used to combine the component image beams. The process proceeds to block 845.
At block 845, a scanner 110, for example a MEMS device with a rotating mirror with two degrees of rotational freedom, for example, two orthogonal planes of rotation, reflects the combined image beam 120 as pseudorandom scanlines sweeping across screen 114. Different methods may be used to inject randomness into the direction of the scanlines from one scan cycle to the next. These methods range from mechanical and physical means, such as imprecisely controlled off-center vibrations at microscopic level, to electronic and software means, such as random number generators. The process proceeds to block 850.
At block 850, detector 112 or another image detection camera optionally detects the reflection of combined image beam 120 from screen 114. In one embodiment, combined image beam 120 is scattered off screen 114 and is refocused onto detector 112, or the other image detection camera, using a lens 510 (see
At decision block 855, the data collected about projected pixel values are compared with the corresponding pixel value of the image stored in memory 118 to determine any deviations. If any deviations are detected, for example, because of screen 114 color or texture, adjustment coefficients for the pixel values of the image in memory 118 are updated at block 860 to adjust such pixel values for the next scan cycle. Otherwise, the process proceeds to block 805 and the process is repeated for the next screen position on the current scanline. As one scanline is completed, another scanline is started and the same process described above is repeated with respect to the new scanline.
High Resolution Scanning
With high (super) resolution scanning of remote surfaces, objects of interest may be cropped and highlighted to accelerate perception of these objects, such as those that may be located on a roadway in front of a vehicle. In this way, vehicular collision avoidance agility may be improved and fast steering responsiveness for the vehicle may be provided. Further, one or more image projection devices may be employed to scan the surface of a road in front of a vehicle (
In one or more embodiments, perception of objects may be improved when the road surface is smooth, without strong sharp edges or structural edge features. Or the road surface coating is uniform providing no obvious image contrast fiducials, and there are no markings that cameras can get “a grip on”. Perhaps a light snow has fallen or a storm has caused just enough snow/dust to cover up any remaining markings on the road surface.
Alternatively, in one or more embodiments, perception of objects may be improved when there are particularly low diffuse light conditions, e.g., winter evening with mist or fog diffusing the available light sources, and/or a low in the sky winter sun, moon light or street lights. Or even worse, the vehicle's headlights are absorbed, scattered and retro-reflected by snow, dust, mist droplets, or rain drops. Further, in one or more embodiments, when a small child, in a white winter coat, a white snow hare, or a pet bunny or other so-called “vulnerable road users” (“VRUs”) cross a road on a dark winter evening, their presence in the path of an oncoming vehicle may not be detected by the typical type of camera used in vision systems for many popular electrically powered vehicles. A VRU may be a person using a road that is not protected by a car chassis or frame, animal pets, pedestrians, bicyclists, and the like. Also, a VRU may be classified as an object based on one or more of a shape, silhouette, motion, or the like.
However, when scanning beams are emanating from a vehicle, a new class of novel “VRU-safe” vehicle, such scanning beams can sharply delineate the outlines of VRUs on the road surface. The sweeping beams can immediately detect the outlines of VRUs. Sweeping across the road within the first 3 to 6 feet directly above the road surface the laser beam's leading edge would detect immediately the left and right edge of any VRU crossing the roads. See
VRU Detection System
In one or more embodiment, when the scanning beam of light, such as a spot, is sweeping the road surface ahead of a vehicle with a rate of 10,000 sweeps per second, which might be done with scanning systems with a 5 kHz resonant scan mirror. In such a VRU system, left to right scans of the beam might alternate between right to left scans. Also, if a full field of view (FoV) of the VRU detection is approx. 50 degrees, then the beams sweeping across this FoV may take approximately 100 microseconds. Also, if a twitchy pixel sensor array includes 1,000 columns, a single reflection of the fast sweeping projected spot beam would cross an individual pixel in the array in approximately 100 nanosecond (100 micro seconds/1000=100 ns). At a distance of 10 meters, the spot beams' motion would sweep across an approximately 10 meters wide FoV (across approximately 3 lanes of traffic) at a rate of 1 centimeter (one pixel, 1/1000th of the 50 degree FoV) per 100 nanoseconds or 1/20th of a millimeter per nanosecond. However, when the beam's leading edge impinges on the VRU edge, the first reflected photons would arrive at least at one of the pixels of at least one of the twitchy pixel arrays in approx. 30 nanoseconds (ToF of 10 meters or 30 feet), and the first avalanche would signify/indicate that a close object is crossing the road within the reach of the sweeping spot beam of laser light. This indication may occur within a millisecond, and in some cases within 1/10 of a millisecond. Note that when the arrivals of the first photons are detected with a temporal resolution of a nanosecond, which is quite easy in the latest SiPM pixel array technologies, then it follows, e.g., in the above example that at a distance of 10 meters ahead of a vehicle (or a robot driver) edges of the VRU can be located to the precision of single millimeter, if desired, which is very significantly beyond the abilities of other sensing systems (such as Cameras and light detection and ranging systems—LIDARS), and is well beyond the acuity of human vision.
In one or more embodiments, an image projection device for scanned (sweeping) laser spot beams of laser light may be configured to scan at least 10 lines across the FoV in a single millisecond. Also, the horizontal scan lines could be arranged to be 10 centimeters apart and thus detect any object greater that 10 centimeters within 1 meter above a surface of a road in front of a vehicle.
In one or more embodiments, scanning an individual point of laser light (spot) the image projection device may be arranged to scan 10 or more points of laser light across the FoV. As long as the points of light are suitably off set from each other by a twitchy pixel array receiver(s), trajectory estimation can quickly track impinging on edges of and progression of the individual points (spot beams) across a remote object such as the VRU. Also, in one or more embodiments, if a VRU detection system employs 10 or more spot beams of laser light simultaneously reflecting off the same scan mirror surface (polygonal, mems, galvanic, or the like) then a scan rate of one sweep across the FoV in one millisecond might be sufficient, thereby enabling a 10 times slower scan rate of 1 kHz (500 Hz back and forth and scan velocity across the same 1000 twitchy pixel columns, at “cadence” or a temporal pitch of approximately 1,000 nano seconds per column.
In one or more embodiments, the VRU detection system may provide highly precise edge detection for locating spatial edges (unmarked walls, corners, pillar and posts). The system can enable detection of a highly (super) resolved and ultra-low latency position, which can be used in determining a location in a six degrees of freedom (DoF) environment, e.g., the system may provide ultra-fast (laser fast) visual angular reckoning (to one 1/100th degree in 3 key rotational degrees of freedom. The VRU detection system can enable flying drones, e.g., Quadcopters, to fly fast in small spaces, as it enables them to instantly detect otherwise hard to detect remote objects, such as small feature objects (birds and wires). The VRU detection system also provides for stabilizing and anchoring augmentation such as feature high lights or labels on real world objects in the FoV of a user, particularly when operating a headset in unstable and challenging inertial environments, such as any athletic activity, such as walking, running, swimming, or the like, or traveling by any type of vehicle, e.g., buses, trains, subways, boats, airplanes, helicopters, motorcycles, cars, or the like.
Additionally, in one or more embodiments, with only 256 columns across and a full sweep across a FoV of 256 columns in 100 microseconds, a “Natural Rhythm”, e.g., the cadence between pixel events regardless of distance, may be approximately 239 microseconds. Although it is unlikely that an edge of the finger aligns with a new pixel, it is somewhat likely to expect three events across the 10-millimeter width of a finger. For example, a first event might be approximately 3 nanoseconds after the sweeping spot beam impinges on a finger, and two more events might occur as the spot on the finger advances enough to enter the two successive pixels across the finger. The exact nanosecond of the first event informs on a precise momentary lateral (achieving resolution, of 1/10th of millimeter or 100 microns with zero motion blur) position of the finger in the path of the scanned spot beam's sweeping direction (lateral sweep direction). The next two events may constitute reflections of the spot beam from two other positions somewhere else on the finger's contiguous surface. Note that if there are multiple fingers with some gaps (best greater than 4 millimeter) than a succession of surfaces and leading edges is instantaneously detected in a single sweep of the scanned spot beam.
In one or more embodiments, random noise events (0+0+0+) and true signal events (++++) may occur concurrently across the twitchy pixel array. Also, the true events (++++) can be sorted, differentiated from the false (noise) events. In this way, the true events fit the signature trajectory left by the fast sweeping scan beam. And the time sequential trail of events is the signature that reveals “how the dots connect”. The events that are (likely) true events t1 t2 . . . t12, t13 are all very close and progressive, and they advance forward at the same rate as the scan direction, i.e. the direction where the cadence is closest to constant.
It will be understood that each block of the flowchart illustration, and combinations of blocks in the flowchart illustration, can be implemented by computer program instructions. These program instructions may be provided to a processor to produce a machine, such that the instructions, which execute on the processor, create means for implementing the actions specified in the flowchart block or blocks. The computer program instructions may be executed by a processor to cause a series of operational steps to be performed by the processor to produce a computer implemented process such that the instructions, which execute on the processor to provide steps for implementing the actions specified in the flowchart block or blocks. The computer program instructions may also cause at least some of the operational steps shown in the blocks of the flowchart to be performed in parallel. Moreover, some of the steps may also be performed across more than one processor, such as might arise in a multi-processor computer system. In addition, one or more blocks or combinations of blocks in the flowchart illustration may also be performed concurrently with other blocks or combinations of blocks, or even in a different sequence than illustrated without departing from the scope or spirit of the invention.
Accordingly, blocks of the flowchart illustration support combinations of means for performing the specified actions, combinations of steps for performing the specified actions and program instruction means for performing the specified actions. It will also be understood that each block of the flowchart illustration, and combinations of blocks in the flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified actions or steps, or combinations of special purpose hardware and computer instructions.
The above specification, examples, and data provide a complete description of the manufacture and use of the composition of the invention. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention resides in the claims hereinafter appended.
This Utility Patent Application is a Continuation of U.S. patent application Ser. No. 17/189,204 filed on Mar. 1, 2021, now U.S. Pat. No. 11,372,320 issued on Jun. 28, 2022, which is based on previously filed U.S. Provisional Patent Application U.S. Ser. No. 63/100,040 filed on Feb. 27, 2020, the benefit of the filing date of which is hereby claimed under 35 U.S.C. § 119(e) and § 120 and the contents of which are each further incorporated in entirety by reference.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4019262 | Breglia et al. | Apr 1977 | A |
| 4340274 | Spooner | Jul 1982 | A |
| 4820041 | Davidson et al. | Apr 1989 | A |
| 4988187 | Kuriyama | Jan 1991 | A |
| 5052820 | McGinniss et al. | Oct 1991 | A |
| 5107122 | Barkan et al. | Apr 1992 | A |
| 5115230 | Smoot | May 1992 | A |
| 5218427 | Koch | Jun 1993 | A |
| 5245398 | Ludden | Sep 1993 | A |
| 5455588 | Lew et al. | Oct 1995 | A |
| 5506682 | Pryor | Apr 1996 | A |
| 5521722 | Colvill et al. | May 1996 | A |
| 5559322 | Jacoby et al. | Sep 1996 | A |
| 5572251 | Ogawa | Nov 1996 | A |
| 5580140 | Katz et al. | Dec 1996 | A |
| 5661506 | Lazzouni et al. | Aug 1997 | A |
| 5793491 | Wangler et al. | Aug 1998 | A |
| 5812664 | Bernobich et al. | Sep 1998 | A |
| 5914783 | Barrus | Jun 1999 | A |
| 5930378 | Kubota et al. | Jul 1999 | A |
| 6009374 | Urahashi | Dec 1999 | A |
| 6115022 | Mayer, III et al. | Sep 2000 | A |
| 6130706 | Hart, Jr. et al. | Oct 2000 | A |
| 6195446 | Skoog | Feb 2001 | B1 |
| 6307526 | Mann | Oct 2001 | B1 |
| 6404416 | Kahn et al. | Jun 2002 | B1 |
| 6535182 | Stanton | Mar 2003 | B2 |
| 6535275 | McCaffrey et al. | Mar 2003 | B2 |
| 6543899 | Covannon et al. | Apr 2003 | B2 |
| 6545670 | Pryor | Apr 2003 | B1 |
| 6670603 | Shimada et al. | Dec 2003 | B2 |
| 6692994 | Davis et al. | Feb 2004 | B2 |
| 6704000 | Carpenter | Mar 2004 | B2 |
| 6710767 | Hasegawa et al. | Mar 2004 | B1 |
| 6766066 | Kitazawa | Jul 2004 | B2 |
| 6843564 | Putilin et al. | Jan 2005 | B2 |
| 6843568 | Schenk et al. | Jan 2005 | B2 |
| 6894823 | Taylor et al. | May 2005 | B2 |
| 6982683 | Stanton | Jan 2006 | B2 |
| 7006142 | Seo | Feb 2006 | B2 |
| 7023536 | Zhang et al. | Apr 2006 | B2 |
| 7027222 | Takahashi et al. | Apr 2006 | B2 |
| 7116455 | Yamaoka | Oct 2006 | B2 |
| 7119965 | Rolland et al. | Oct 2006 | B1 |
| 7144117 | Kojima | Dec 2006 | B2 |
| 7182465 | Fuchs et al. | Feb 2007 | B2 |
| 7203383 | Fisher | Apr 2007 | B2 |
| 7232229 | Peeters et al. | Jun 2007 | B2 |
| 7262765 | Brown et al. | Aug 2007 | B2 |
| 7278745 | Engle | Oct 2007 | B2 |
| 7280211 | Horibe et al. | Oct 2007 | B2 |
| 7283301 | Peeters et al. | Oct 2007 | B2 |
| 7289110 | Hansson | Oct 2007 | B2 |
| 7303289 | Fujiwara | Dec 2007 | B2 |
| 7348528 | Marshall | Mar 2008 | B2 |
| 7349553 | Rodriguez | Mar 2008 | B2 |
| 7359041 | Xie et al. | Apr 2008 | B2 |
| 7375804 | Liebman et al. | May 2008 | B2 |
| 7377656 | Nojima et al. | May 2008 | B2 |
| 7401920 | Kranz et al. | Jul 2008 | B1 |
| 7440691 | Beniyama et al. | Oct 2008 | B2 |
| 7511847 | Silverbrook et al. | Mar 2009 | B2 |
| 7554652 | Babin et al. | Jun 2009 | B1 |
| 7667598 | Yenisch et al. | Feb 2010 | B2 |
| 7787134 | Kohnen et al. | Aug 2010 | B2 |
| 7905567 | Orsley | Mar 2011 | B2 |
| 7911444 | Yee | Mar 2011 | B2 |
| 8115728 | Feng | Feb 2012 | B2 |
| 8169447 | Bhogal et al. | May 2012 | B2 |
| 8170329 | Seko et al. | May 2012 | B2 |
| 8189176 | Moir | May 2012 | B2 |
| 8213022 | Riza et al. | Jul 2012 | B1 |
| 8259239 | Hua | Sep 2012 | B2 |
| 8282222 | Smits | Oct 2012 | B2 |
| 8297758 | Choi et al. | Oct 2012 | B2 |
| 8330942 | Nordenfelt et al. | Dec 2012 | B2 |
| 8355117 | Niclass | Jan 2013 | B2 |
| 8430512 | Smits | Apr 2013 | B2 |
| 8493573 | Chinn et al. | Jul 2013 | B2 |
| 8558810 | Guo | Oct 2013 | B2 |
| 8573783 | Smits | Nov 2013 | B2 |
| 8636367 | Callison et al. | Jan 2014 | B1 |
| 8665435 | Hidaka | Mar 2014 | B2 |
| 8696141 | Smits | Apr 2014 | B2 |
| 8711370 | Smits | Apr 2014 | B1 |
| 8718326 | Yoon et al. | May 2014 | B2 |
| 8723928 | Moriyama et al. | May 2014 | B2 |
| 8773512 | Rafii | Jul 2014 | B1 |
| 8780161 | Samadani et al. | Jul 2014 | B2 |
| 8797531 | Knox et al. | Aug 2014 | B2 |
| 8867827 | Yeatman, Jr. et al. | Oct 2014 | B2 |
| 8941817 | Laudrain et al. | Jan 2015 | B2 |
| 8947755 | Konuma et al. | Feb 2015 | B2 |
| 8953242 | Larson et al. | Feb 2015 | B2 |
| 8957847 | Karakotsios et al. | Feb 2015 | B1 |
| 8994780 | Moore | Mar 2015 | B2 |
| 9026596 | Perez et al. | May 2015 | B2 |
| 9045226 | Piasecki et al. | Jun 2015 | B2 |
| 9080866 | Dowdall et al. | Jul 2015 | B1 |
| 9097800 | Zhu | Aug 2015 | B1 |
| 9131192 | Ubillos et al. | Sep 2015 | B2 |
| 9134799 | Mark | Sep 2015 | B2 |
| 9151607 | Davies et al. | Oct 2015 | B2 |
| 9244339 | Wang | Jan 2016 | B2 |
| 9323055 | Baillot | Apr 2016 | B2 |
| 9366519 | Danbury et al. | Jun 2016 | B2 |
| 9377533 | Smits | Jun 2016 | B2 |
| 9392225 | Eisenberg | Jul 2016 | B2 |
| 9454014 | Kurashige et al. | Sep 2016 | B2 |
| 9482514 | Bridges | Nov 2016 | B2 |
| 9562764 | France | Feb 2017 | B2 |
| 9581883 | Smits | Feb 2017 | B2 |
| 9599713 | Giger et al. | Mar 2017 | B2 |
| 9618610 | Kao et al. | Apr 2017 | B2 |
| 9703473 | Schillings et al. | Jul 2017 | B2 |
| 9813673 | Smits | Nov 2017 | B2 |
| 9854196 | Liu et al. | Dec 2017 | B2 |
| 9864440 | Geller et al. | Jan 2018 | B2 |
| 9939233 | Scott et al. | Apr 2018 | B2 |
| 9946076 | Smits et al. | Apr 2018 | B2 |
| 9952033 | Martini et al. | Apr 2018 | B2 |
| 9961337 | Stroetmann | May 2018 | B2 |
| 10037017 | Wooldridge et al. | Jul 2018 | B2 |
| 10052927 | Maise et al. | Aug 2018 | B2 |
| 10067230 | Smits | Sep 2018 | B2 |
| 10261183 | Smits | Apr 2019 | B2 |
| 10331021 | Smits | Jun 2019 | B2 |
| 10564284 | Smits | Feb 2020 | B2 |
| 10614734 | Peuhkurinen | Apr 2020 | B2 |
| 10962867 | Smits | Mar 2021 | B2 |
| 20010043165 | Stanton | Nov 2001 | A1 |
| 20020011987 | Kitazawa | Jan 2002 | A1 |
| 20020036765 | McCaffrey et al. | Mar 2002 | A1 |
| 20020039138 | Edelson et al. | Apr 2002 | A1 |
| 20020040971 | Ono | Apr 2002 | A1 |
| 20020067466 | Covannon et al. | Jun 2002 | A1 |
| 20020089489 | Carpenter | Jul 2002 | A1 |
| 20020100884 | Maddock | Aug 2002 | A1 |
| 20020139920 | Seibel et al. | Oct 2002 | A1 |
| 20020145588 | McCahon et al. | Oct 2002 | A1 |
| 20020149694 | Seo | Oct 2002 | A1 |
| 20030010888 | Shimada et al. | Jan 2003 | A1 |
| 20030045034 | Davis et al. | Mar 2003 | A1 |
| 20030156260 | Putilin et al. | Aug 2003 | A1 |
| 20030202234 | Taylor et al. | Oct 2003 | A1 |
| 20030202679 | Rodriguez | Oct 2003 | A1 |
| 20030214710 | Takahashi et al. | Nov 2003 | A1 |
| 20030222849 | Starkweather | Dec 2003 | A1 |
| 20040003409 | Berstis | Jan 2004 | A1 |
| 20040006424 | Joyce et al. | Jan 2004 | A1 |
| 20040041996 | Abe | Mar 2004 | A1 |
| 20040054359 | Ruiz et al. | Mar 2004 | A1 |
| 20040100508 | Hansson | May 2004 | A1 |
| 20040114834 | Fisher | Jun 2004 | A1 |
| 20040179254 | Lewis et al. | Sep 2004 | A1 |
| 20040218155 | Schenk et al. | Nov 2004 | A1 |
| 20040240754 | Smith et al. | Dec 2004 | A1 |
| 20040263874 | Silverbrook et al. | Dec 2004 | A1 |
| 20050024586 | Teiwes et al. | Feb 2005 | A1 |
| 20050030305 | Brown et al. | Feb 2005 | A1 |
| 20050035943 | Kojima | Feb 2005 | A1 |
| 20050052635 | Xie et al. | Mar 2005 | A1 |
| 20050083248 | Biocca et al. | Apr 2005 | A1 |
| 20050099664 | Yamaoka | May 2005 | A1 |
| 20050159893 | Isaji et al. | Jul 2005 | A1 |
| 20050195375 | Fujiwara | Sep 2005 | A1 |
| 20050195387 | Zhang et al. | Sep 2005 | A1 |
| 20050219530 | Horibe et al. | Oct 2005 | A1 |
| 20050254726 | Fuchs et al. | Nov 2005 | A1 |
| 20050273830 | Silver et al. | Dec 2005 | A1 |
| 20060028328 | Cresse | Feb 2006 | A1 |
| 20060028374 | Fullerton | Feb 2006 | A1 |
| 20060028375 | Honda et al. | Feb 2006 | A1 |
| 20060028622 | Nojima et al. | Feb 2006 | A1 |
| 20060132447 | Conrad | Jun 2006 | A1 |
| 20060132472 | Peeters et al. | Jun 2006 | A1 |
| 20060132729 | Engle | Jun 2006 | A1 |
| 20060197936 | Liebman et al. | Sep 2006 | A1 |
| 20060256133 | Rosenberg | Nov 2006 | A1 |
| 20070046625 | Yee | Mar 2007 | A1 |
| 20070053679 | Beniyama et al. | Mar 2007 | A1 |
| 20070064242 | Childers | Mar 2007 | A1 |
| 20070103699 | Kohnen et al. | May 2007 | A1 |
| 20070138371 | Marshall | Jun 2007 | A1 |
| 20070182949 | Niclass | Aug 2007 | A1 |
| 20070211329 | Haase et al. | Sep 2007 | A1 |
| 20070273610 | Baillot | Nov 2007 | A1 |
| 20080018591 | Pittel et al. | Jan 2008 | A1 |
| 20080174516 | Xiao et al. | Jul 2008 | A1 |
| 20080266169 | Akita | Oct 2008 | A1 |
| 20080291213 | Bhogal et al. | Nov 2008 | A1 |
| 20080309913 | Fallon | Dec 2008 | A1 |
| 20080316026 | Yenisch et al. | Dec 2008 | A1 |
| 20080317077 | Hoving et al. | Dec 2008 | A1 |
| 20090096994 | Smits | Apr 2009 | A1 |
| 20090147239 | Zhu et al. | Jun 2009 | A1 |
| 20090285590 | Orsley | Nov 2009 | A1 |
| 20100002154 | Hua | Jan 2010 | A1 |
| 20100008588 | Feldkhun et al. | Jan 2010 | A1 |
| 20100013860 | Mandella et al. | Jan 2010 | A1 |
| 20100014750 | Seko et al. | Jan 2010 | A1 |
| 20100045967 | Moir | Feb 2010 | A1 |
| 20100110385 | Choi et al. | May 2010 | A1 |
| 20100142856 | Takeuchi et al. | Jun 2010 | A1 |
| 20100149518 | Nordenfelt et al. | Jun 2010 | A1 |
| 20100235006 | Brown | Sep 2010 | A1 |
| 20100246902 | Rowe et al. | Sep 2010 | A1 |
| 20100305857 | Byrne et al. | Dec 2010 | A1 |
| 20100326311 | Simon | Dec 2010 | A1 |
| 20100328054 | Yim et al. | Dec 2010 | A1 |
| 20110001793 | Moriyama et al. | Jan 2011 | A1 |
| 20110102763 | Brown et al. | May 2011 | A1 |
| 20110115747 | Powell et al. | May 2011 | A1 |
| 20110123113 | Berretty et al. | May 2011 | A1 |
| 20110211243 | Smits | Sep 2011 | A1 |
| 20110249157 | Fredembach et al. | Oct 2011 | A1 |
| 20110304842 | Kao et al. | Dec 2011 | A1 |
| 20120017147 | Mark | Jan 2012 | A1 |
| 20120050528 | Davies et al. | Mar 2012 | A1 |
| 20120132713 | Chaum | May 2012 | A1 |
| 20120134537 | Yoon et al. | May 2012 | A1 |
| 20120140231 | Knox et al. | Jun 2012 | A1 |
| 20120187296 | Hollander et al. | Jul 2012 | A1 |
| 20120224019 | Samadani et al. | Sep 2012 | A1 |
| 20120229818 | Chinn et al. | Sep 2012 | A1 |
| 20120236379 | da Silva et al. | Sep 2012 | A1 |
| 20120250152 | Larson et al. | Oct 2012 | A1 |
| 20120262696 | Eisele et al. | Oct 2012 | A1 |
| 20120274937 | Hays et al. | Nov 2012 | A1 |
| 20120320013 | Perez et al. | Dec 2012 | A1 |
| 20130003081 | Smits | Jan 2013 | A1 |
| 20130021271 | Guo | Jan 2013 | A1 |
| 20130079983 | Ehlgen et al. | Mar 2013 | A1 |
| 20130088465 | Geller et al. | Apr 2013 | A1 |
| 20130135198 | Hodge et al. | May 2013 | A1 |
| 20130170006 | Kurashige et al. | Jul 2013 | A1 |
| 20130176561 | Hidaka | Jul 2013 | A1 |
| 20130215487 | Konuma et al. | Aug 2013 | A1 |
| 20130229669 | Smits | Sep 2013 | A1 |
| 20130239057 | Ubillos et al. | Sep 2013 | A1 |
| 20130258108 | Ono et al. | Oct 2013 | A1 |
| 20130293396 | Selevan | Nov 2013 | A1 |
| 20130293760 | Nisenzon et al. | Nov 2013 | A1 |
| 20130300637 | Smits et al. | Nov 2013 | A1 |
| 20130300670 | Besperstov et al. | Nov 2013 | A1 |
| 20130342813 | Wang | Dec 2013 | A1 |
| 20140022539 | France | Jan 2014 | A1 |
| 20140098179 | Moore | Apr 2014 | A1 |
| 20140146243 | Liu et al. | May 2014 | A1 |
| 20140176954 | Scott et al. | Jun 2014 | A1 |
| 20140204385 | Ouyang et al. | Jul 2014 | A1 |
| 20140215841 | Danbury et al. | Aug 2014 | A1 |
| 20140267620 | Bridges | Sep 2014 | A1 |
| 20140273752 | Bajaj et al. | Sep 2014 | A1 |
| 20140284457 | Smits | Sep 2014 | A1 |
| 20140285818 | Holz | Sep 2014 | A1 |
| 20140307248 | Giger et al. | Oct 2014 | A1 |
| 20140350836 | Stettner et al. | Nov 2014 | A1 |
| 20140354514 | Aronsson | Dec 2014 | A1 |
| 20150009493 | Kwiatkowski et al. | Jan 2015 | A1 |
| 20150066196 | Wooldridge et al. | Mar 2015 | A1 |
| 20150091815 | Michaelis | Apr 2015 | A1 |
| 20150233703 | Martini et al. | Apr 2015 | A1 |
| 20150160332 | Sebastian et al. | Jun 2015 | A1 |
| 20150169082 | Li et al. | Jun 2015 | A1 |
| 20150225783 | Mears et al. | Aug 2015 | A1 |
| 20150279114 | Yonekubo | Oct 2015 | A1 |
| 20150285625 | Deane | Oct 2015 | A1 |
| 20150286293 | Gruhlke et al. | Oct 2015 | A1 |
| 20150301180 | Stettner et al. | Oct 2015 | A1 |
| 20160004126 | Leister | Jan 2016 | A1 |
| 20160011312 | Leyva | Jan 2016 | A1 |
| 20160014403 | Stroetmann | Jan 2016 | A1 |
| 20160041266 | Smits | Feb 2016 | A1 |
| 20160047895 | Dussan | Feb 2016 | A1 |
| 20160050345 | Longbotham et al. | Feb 2016 | A1 |
| 20160139266 | Montoya et al. | May 2016 | A1 |
| 20160162747 | Singh et al. | Jun 2016 | A1 |
| 20160259038 | Retterath et al. | Sep 2016 | A1 |
| 20160259058 | Verheggen et al. | Sep 2016 | A1 |
| 20160282468 | Gruver et al. | Sep 2016 | A1 |
| 20160306044 | Smits | Oct 2016 | A1 |
| 20160313553 | Song et al. | Oct 2016 | A1 |
| 20160335778 | Smits | Nov 2016 | A1 |
| 20160349526 | Kurashige et al. | Dec 2016 | A1 |
| 20170003392 | Bartlett et al. | Jan 2017 | A1 |
| 20170010104 | Aviel | Jan 2017 | A1 |
| 20170045358 | Masuda et al. | Feb 2017 | A1 |
| 20170052065 | Sharma et al. | Feb 2017 | A1 |
| 20170097407 | Shpunt et al. | Apr 2017 | A1 |
| 20170108443 | Kurihara et al. | Apr 2017 | A1 |
| 20170131090 | Bronstein et al. | May 2017 | A1 |
| 20170176575 | Smits | Jun 2017 | A1 |
| 20170176596 | Shpunt et al. | Jun 2017 | A1 |
| 20170208292 | Smits | Jul 2017 | A1 |
| 20170242104 | Dussan | Aug 2017 | A1 |
| 20170299721 | Eichenholz et al. | Oct 2017 | A1 |
| 20170363724 | Reid | Dec 2017 | A1 |
| 20180039852 | Nakamura et al. | Feb 2018 | A1 |
| 20180113216 | Kremer et al. | Apr 2018 | A1 |
| 20180120931 | Shpunt et al. | May 2018 | A1 |
| 20180180733 | Smits | Jun 2018 | A1 |
| 20180189574 | Brueckner et al. | Jul 2018 | A1 |
| 20190011567 | Pacala et al. | Jan 2019 | A1 |
| 20190080612 | Weissman et al. | Mar 2019 | A1 |
| 20190285877 | Ogino | Sep 2019 | A1 |
| 20200013185 | Yoshimura | Jan 2020 | A1 |
| 20200132984 | Tsao et al. | Apr 2020 | A1 |
| 20200133106 | Smits | Apr 2020 | A1 |
| 20200142064 | Davis | May 2020 | A1 |
| 20200192082 | Zhou | Jun 2020 | A1 |
| 20200310114 | Tanabe | Oct 2020 | A1 |
| 20210011132 | Ellis | Jan 2021 | A1 |
| 20210157012 | Wajnberg et al. | May 2021 | A1 |
| Number | Date | Country |
|---|---|---|
| 1633801 | Jun 2005 | CN |
| 1902530 | Jan 2007 | CN |
| 201159795 | Dec 2008 | CN |
| 101750012 | Jun 2010 | CN |
| 102084290 | Jun 2011 | CN |
| 102576156 | Jul 2012 | CN |
| 103608642 | Feb 2014 | CN |
| 103797328 | May 2014 | CN |
| 105066953 | Nov 2015 | CN |
| 102015205826 | Oct 2015 | DE |
| 0583060 | Feb 1994 | EP |
| 0722109 | Jul 1996 | EP |
| 1213597 | Jun 2002 | EP |
| 2148220 | Jan 2010 | EP |
| 2711667 | Mar 2014 | EP |
| 2510001 | Jul 2017 | GB |
| 11119184 | Apr 1999 | JP |
| 2000-304508 | Nov 2000 | JP |
| 201045381 | Feb 2001 | JP |
| 2003029201 | Jan 2003 | JP |
| 2004132914 | Apr 2004 | JP |
| 2005519338 | Jun 2005 | JP |
| 2010-197227 | Sep 2010 | JP |
| 2011197674 | Oct 2011 | JP |
| 2013097138 | May 2013 | JP |
| 2015-025901 | Feb 2015 | JP |
| 10-2011-0115752 | Oct 2011 | KR |
| 101665938 | Oct 2016 | KR |
| 1992018971 | Oct 1992 | WO |
| 200034818 | Jun 2000 | WO |
| 2002004247 | Jan 2002 | WO |
| 2002037166 | May 2002 | WO |
| 2005010739 | Feb 2005 | WO |
| 2006063577 | Jun 2006 | WO |
| 2008152647 | Dec 2008 | WO |
| 2009049272 | Apr 2009 | WO |
| 2011109402 | Sep 2011 | WO |
| 2012054231 | Apr 2012 | WO |
| 2013079099 | Jun 2013 | WO |
| 2014141115 | Sep 2014 | WO |
| 2016033036 | Mar 2016 | WO |
| 2016130997 | Aug 2016 | WO |
| 2016168378 | Oct 2016 | WO |
| 2017040066 | Mar 2017 | WO |
| 2017106875 | Jun 2017 | WO |
| Entry |
|---|
| Office Communication for Japanese Patent Application No. JP 2019-535248 dated Jul. 4, 2022, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Jul. 18, 2022, pp. 1-5. |
| Office Communication for U.S. Appl. No. 17/214,505 dated Aug. 26, 2022, pp. 1-13. |
| Office Communication for U.S. Appl. No. 16/708,198 dated Aug. 26, 2022, pp. 1-5. |
| Office Communication for U.S. Appl. No. 17/214,505 dated Sep. 12, 2022, pp. 1-2. |
| Examination Report for European Patent Application No. 20201393.4 dated Sep. 15, 2022, pp. 1-6. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Nov. 10, 2022, pp. 1-7. |
| Office Communication for U.S. Appl. No. 17/187,069 dated Dec. 5, 2022, pp. 1-11. |
| Office Communication for Chinese Patent Application No. 201780084810.1 dated Nov. 22, 2022, pp. 1-21. |
| Mak, D.K., “Locating Flaws in Three-Dimensional Space Using a Transmitter-Receiver System,” NDT, Nov. 1990, vol. 12, No. 11, pp. 1-9. |
| Gu, Liming, “Research on Key Technologies of Photon Beam Position Measurement at HLS,” A dissertation for Doctor's degree, University of Science and Technology of China, May 2011, pp. 1-248. |
| Chen, Junqing et al., “Digital Camera Imaging System Simulation,” IEEE Transactions on Electron Devices, Nov. 2009, vol. 56, Iss. 11, pp. 2496-2505. |
| Office Communication for Chinese Patent Application No. 201780076900.6 dated Dec. 5, 2022, pp. 1-15. |
| Office Communication for Japanese Patent Application No. JP 2019-535248 dated Jan. 10, 2023, pp. 1-4. |
| Office Communication for U.S. Appl. No. 16/938,968 dated Jan. 26, 2023, pp. 1-11. |
| Office Communication for U.S. Appl. No. 16/708,198 dated Mar. 6, 2023, pp. 1-5. |
| Office Communication for U.S. Appl. No. 16/790,592 dated Mar. 8, 2023, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Apr. 25, 2023, pp. 1-6. |
| Office Communication for U.S. Appl. No. 17/188,483 dated May 22, 2023, pp. 1-10. |
| Office Communication for U.S. Appl. No. 12/249,899 dated Jun. 6, 2012, pp. 1-12. |
| Office Communication for U.S. Appl. No. 12/249,899 dated Mar. 13, 2012, pp. 1-12. |
| Office Communication for U.S. Appl. No. 12/249,899 dated Sep. 14, 2011, pp. 1-12. |
| Extended European Search Report for European Patent Application No. 08837063.0 dated Nov. 19, 2010, pp. 1-8. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2008/079663 dated Apr. 30, 2009, pp. 1-5. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2011/026691 dated Oct. 24, 2011, pp. 1-7. |
| International Search Report for International Patent Application No. PCT/US2011/054751 dated Jan. 30, 2012, p. 1. |
| International Preliminary Report on Patentability for International Patent Application No. PCT/US2008/079663 dated Jan. 25, 2010, pp. 1-11. |
| Examination Report for European Patent Application No. 08837063.0 dated Oct. 22, 2012, pp. 1-6. |
| Examination Report for European Patent Application No. 08837063.0 dated Dec. 27, 2011, pp. 1-5. |
| International Preliminary Report on Patentability issued for International Patent Application No. PCT/US2011/026691 dated Sep. 4, 2012, pp. 1-7. |
| International Preliminary Report on Patentability issued for International Patent Application No. PCT/US2011/054751 dated Apr. 9, 2013, pp. 1-7. |
| Office Communication for U.S. Appl. No. 13/037,949 dated Nov. 2, 2012, pp. 1-13. |
| Office Communication U.S. Appl. No. 13/037,949 dated Aug. 26, 2013, pp. 1-9. |
| Office Communication for U.S. Appl. No. 13/605,948 dated Dec. 31, 2012, pp. 1-11. |
| Office Communication for U.S. Appl. No. 14/046,374 dated Feb. 20, 2014, pp. 1-10. |
| Extended European Search Report for European Patent Application No. 11834848.1 dated Feb. 21, 2014, pp. 1-7. |
| Savage, Phil, “GDC 2013: Valv's Michael Abrash on the challenges of VR—‘a new world is emerging’, ” PCGamer, Apr. 2, 2013, pp. 1-6. |
| Office Communication for U.S. Appl. No. 13/858,762 dated Sep. 13, 2013, pp. 1-18. |
| Office Communication for U.S. Appl. No. 13/858,762 dated Jan. 31, 2014, pp. 1-15. |
| Office Communication for U.S. Appl. No. 14/048,954 dated Feb. 26, 2014, pp. 1-15. |
| Office Communication for U.S. Appl. No. 14/048,954 dated Oct. 22, 2014, pp. 1-8. |
| Office Communication for U.S. Appl. No. 13/877,652 dated Mar. 12, 2015, pp. 1-20. |
| Office Communication for U.S. Appl. No. 14/636,062 dated Jun. 2, 2015, pp. 1-7. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2015/023184 dated Jun. 29, 2015, pp. 1-13. |
| Office Communication for U.S. Appl. No. 13/877,652 dated Aug. 18, 2015, pp. 1-21. |
| Office Communication U.S. Appl. No. 14/636,062 dated Sep. 25, 2015, pp. 1-8. |
| Office Communication for U.S. Appl. No. 14/671,904 dated Sep. 22, 2015, pp. 1-15. |
| Office Communication for U.S. Appl. No. 14/823,668 dated Oct. 30, 2015, pp. 1-12. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2015/044691 dated Nov. 18, 2015, pp. 1-12. |
| Office Communication for U.S. Appl. No. 14/636,062 dated Dec. 14, 2015, pp. 1-3. |
| Office Communication for U.S. Appl. No. 14/636,062 dated Feb. 1, 2016, pp. 1-9. |
| Office Communication for U.S. Appl. No. 13/877,652 dated Feb. 10, 2016, pp. 1-22. |
| Office Communication for U.S. Appl. No. 14/671,904 dated Feb. 22, 2016, pp. 1-13. |
| Office Communication for U.S. Appl. No. 14/823,668 dated Feb. 24, 2016, pp. 1-15. |
| O'Toole, Matthew et al., “Homogeneous Codes for Energy-Efficient Illumination and Imaging,” ACM Transactions on Graphics, Jul. 2015, vol. 34(4), pp. 1-13. |
| Office Communication for U.S. Appl. No. 14/823,668 dated May 18, 2016, pp. 1-10. |
| Office Communication for U.S. Appl. No. 14/218,643 dated Jun. 23, 2016, pp. 1-11. |
| Office Communication for U.S. Appl. No. 13/877,652 dated Aug. 12, 2016, pp. 1-22. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Aug. 19, 2016, pp. 1-12. |
| Office Communication for U.S. Appl. No. 14/636,062 dated Aug. 24, 2016, pp. 1-9. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2016/027386 dated Aug. 26, 2016, pp. 1-10. |
| Office Communication for U.S. Appl. No. 14/671,904 dated Sep. 28, 2016, pp. 1-14. |
| Office Communication for U.S. Appl. No. 14/218,643 dated Nov. 1, 2016, pp. 1-10. |
| Kanzawa, Yusuke et al., “Human Skin Detection by Visible and Near-Infrared Imaging,” IAPR Conference on Machine Vision Applications, Jun. 13-15, 2011, Nara Japan, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/384,227 dated Feb. 7, 2017, pp. 1-8. |
| Blais, F. et al., “Range Error Analysis of an Integrated Time-of-Flight, Triangulation, and Photogrammetry 3D Laser Scanning System,” SPIE Proceedings of Aero Sense, Orlando, Florida, Apr. 24-28, 2000, vol. 4035, pp. 1-14. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Mar. 9, 2017, pp. 1-7. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2016/067626 dated Mar. 16, 2017, pp. 1-12. |
| Office Communication for U.S. Appl. No. 14/671,904 dated May 5, 2017, pp. 1-11. |
| Office Communication for U.S. Appl. No. 16/820,523 dated Apr. 22, 2020, pp. 1-10. |
| Extended European Search Report for European Patent Application No. 17742125.2 dated Jul. 29, 2019, pp. 1-13. |
| Li, Hao et al., “Facial Performance Sensing Head-Mounted Display.” ACM Transactions on Graphics (TOG), vol. 34, No. 4, 2015, pp. 1-9. |
| Seymour, Mike, “Facing Second Son—fxguide,” Feb. 2, 2015, https://www.fxguide.com/fxfeatured/facing-second-son/, retrieved on Jul. 19, 2019, pp. 1-18. |
| Rolland, Jannick P. et al., “Development of Head-Mounted Projection Displays for Distributed, Collaborative, Augmented Reality Applications.” Presence: Teleoperators & Virtual Environments, vol. 14, No. 5, 2005, pp. 528-549. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2019/015739 dated May 17, 2019, pp. 1-7. |
| Extended European Search Report for European Patent Application No. 17878671.1 dated May 7, 2020, pp. 1-11. |
| Examination Report for European Patent Application No. 16876940.4 dated May 28, 2020, pp. 1-5. |
| Office Communication for U.S. Appl. No. 16/435,392 dated Aug. 10, 2020, pp. 1-7. |
| Office Communication for U.S. Appl. No. 16/679,110 dated Aug. 18, 2020, pp. 1-9. |
| Office Communication for U.S. Appl. No. 16/443,702 dated Sep. 18, 2020, pp. 1-14. |
| Office Communication for U.S. Appl. No. 16/435,392 dated Oct. 23, 2020, pp. 1-4. |
| Office Communication for Japanese Patent Application No. JP 2018551896 dated Oct. 26, 2020, pp. 1-11. |
| Office Communication for U.S. Appl. No. 16/820,523 dated Nov. 2, 2020, pp. 1-6. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Nov. 4, 2020, pp. 1-16. |
| Office Communication for U.S. Appl. No. 16/659,513 dated Nov. 25, 2020, pp. 1-6. |
| Office Communication for U.S. Appl. No. 16/435,392 dated Dec. 1, 2020, pp. 1-13. |
| Office Communication for U.S. Appl. No. 16/679,110 dated Dec. 7, 2020, pp. 1-6. |
| Office Communication for U.S. Appl. No. 16/443,702 dated Dec. 18, 2020, pp. 1-3. |
| Partial Supplementary European Search Report for European Patent Application No. 18797782.2 dated Jan. 19, 2021, pp. 1-19. |
| Office Communication for U.S. Appl. No. 16/443,702 dated Feb. 8, 2021, pp. 1-12. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Mar. 17, 2021, pp. 1-10. |
| Office Communication for U.S. Appl. No. 16/679,110 dated Mar. 17, 2021, pp. 1-8. |
| Extended European Search Report for European Patent Application No. 20201393.4 dated Apr. 22, 2021, pp. 1-9. |
| Duchowski, Andrew T. et al., “Gaze-Contingent Displays: A Review,” Cyberpsychology & Behavior, 2004, vol. 7, No. 6, pp. 621-634. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2021/020359 dated May 11, 2021, pp. 1-7. |
| Office Communication for U.S. Appl. No. 16/443,702 dated Jun. 1, 2021, pp. 1-5. |
| Examination Report for European Patent Application No. 17878671.1 dated May 14, 2021, pp. 1-5. |
| Extended European Search Report for European Patent Application No. 18797782.2 dated May 27, 2021, pp. 1-21. |
| Examination Report for European Patent Application No. 11834848.1 dated Jun. 7, 2019, pp. 1-6. |
| Examination Report for European Patent Application No. 17742125.2 dated Nov. 19, 2020, pp. 1-7. |
| Office Communication for Chinese Patent Application No. 201880030862.5 dated Jun. 9, 2021, pp. 1-23. |
| Examination Report for European Patent Application No. 16876940.4 dated Jul. 30, 2021, pp. 1-4. |
| Extended European Search Report for European Patent Application No. 17885850.2 dated May 25, 2020, pp. 1-8. |
| Examination Report for European Patent Application No. 17885850.2 dated Aug. 30, 2021, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Oct. 5, 2021, pp. 1-20. |
| Office Communication for Japanese Patent Application No. JP 2019-535248 dated Nov. 17, 2021, pp. 1-7. |
| Kasai, Takeshi et al., “A Real Time Measurement System of 3-D Motion Using Multiple Cameras,” Society of Biomechanisms Japan, 1986, vol. 8, pp. 1-32. |
| Office Communication for Chinese Patent Application No. 201680082143.9 dated Nov. 30, 2021, pp. 1-33. |
| Office Communication for U.S. Appl. No. 15/411,959 dated May 11, 2017, pp. 1-9. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2017/014616 dated May 1, 2017, pp. 1-11. |
| Office Communication for U.S. Appl. No. 13/877,652 dated May 31, 2017, pp. 1-23. |
| Office Communication for U.S. Appl. No. 15/384,227 dated Jul. 19, 2017, pp. 1-5. |
| Office Communication for U.S. Appl. No. 14/671,904 dated Aug. 18, 2017, pp. 1-7. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Aug. 15, 2017, pp. 1-7. |
| Office Communication for U.S. Appl. No. 15/411,959 dated Aug. 29, 2017, pp. 1-5. |
| Office Communication for U.S. Appl. No. 13/877,652 dated Dec. 6, 2017, pp. 1-8. |
| Office Communication for U.S. Appl. No. 15/799,149 dated Jan. 10, 2018, pp. 1-7. |
| Office Communication for U.S. Appl. No. 15/444,182 dated Feb. 14, 2018, pp. 1-8. |
| Office Communication for U.S. Appl. No. 15/804,392 dated Feb. 9, 2018, pp. 1-10. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Feb. 12, 2018, pp. 1-9. |
| Office Communication for U.S. Appl. No. 15/804,909 dated Feb. 12, 2018, pp. 1-14. |
| Office Communication for U.S. Appl. No. 15/098,285 dated Apr. 19, 2018, pp. 1-20. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2017/068377 dated Apr. 17, 2018, pp. 1-12. |
| Office Communication for U.S. Appl. No. 15/694,532 dated Jul. 10, 2018, pp. 1-6. |
| Office Communication for U.S. Appl. No. 15/804,392 dated Jun. 6, 2018, pp. 1-7. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Jun. 11, 2018, pp. 1-9. |
| Office Communication for U.S. Appl. No. 15/804,909 dated Jul. 5, 2018, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/799,149 dated Jun. 20, 2018, pp. 1-3. |
| Office Communication for U.S. Appl. No. 15/853,783 dated Aug. 15, 2018, pp. 1-10. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2017/059282 dated Aug. 10, 2018, pp. 1-10. |
| Office Communication for U.S. Appl. No. 15/444,182 dated Sep. 13, 2018, pp. 1-8. |
| Office Communication for U.S. Appl. No. 16/049,380 dated Sep. 27, 2018, pp. 1-15. |
| Office Communication for U.S. Appl. No. 16/140,485 dated Nov. 23, 2018, pp. 1-23. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2018/032078 dated Nov. 16, 2018, pp. 1-16. |
| Office Communication for U.S. Appl. No. 15/194,502 dated Jan. 3, 2019, pp. 1-11. |
| Office Communication for U.S. Appl. No. 15/694,532 dated Jan. 17, 2019, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/853,783 dated Jan. 24, 2019, pp. 1-6. |
| Office Communication for U.S. Appl. No. 15/444,182 dated Mar. 20, 2019, pp. 1-10. |
| Office Communication U.S. Appl. No. 15/194,502 dated Mar. 6, 2019, pp. 1-8. |
| Office Communication for U.S. Appl. No. 16/223,043 dated Mar. 14, 2019, pp. 1-17. |
| Office Communication for U.S. Appl. No. 15/976,269 dated Mar. 25, 2019, pp. 1-13. |
| Office Communication for U.S. Appl. No. 16/165,631 dated Apr. 1, 2019, pp. 1-9. |
| Office Communication for U.S. Appl. No. 16/114,139 dated Apr. 19, 2019, pp. 1-17. |
| Office Communication for U.S. Appl. No. 16/398,139 dated Jun. 6, 2019, pp. 1-5. |
| Office Communication for U.S. Appl. No. 16/140,485 dated Jun. 3, 2019, pp. 1-14. |
| Office Communication for U.S. Appl. No. 15/976,269 dated Jul. 8, 2019, pp. 1-5. |
| Office Communication for U.S. Appl. No. 16/384,761 dated Jun. 21, 2019, pp. 1-11. |
| Office Communication for U.S. Appl. No. 16/261,528 dated May 17, 2019, pp. 1-9. |
| Office Communication for U.S. Appl. No. 16/165,631 dated Jul. 19, 2019, pp. 1-10. |
| International Search Report and Written Opinion for International Patent Application No. PCT/US2018/056757 dated Mar. 11, 2019, pp. 1-12. |
| Extended European Search Report for European Patent Application No. 16876940.4 dated May 8, 2019, pp. 1-8. |
| Office Communication for U.S. Appl. No. 16/140,485 dated Aug. 9, 2019, pp. 1-3. |
| Office Communication for U.S. Appl. No. 16/114,139 dated Aug. 2, 2019, pp. 1-7. |
| Office Communication for U.S. Appl. No. 16/140,845 dated Sep. 20, 2019, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/976,269 dated Sep. 6, 2019, pp. 1-7. |
| Office Communication for U.S. Appl. No. 16/443,702 dated Oct. 3, 2019, pp. 1-13. |
| Office Communication for U.S. Appl. No. 16/398,139 dated Sep. 27, 2019, pp. 1-7. |
| Office Communication for U.S. Appl. No. 16/530,818 dated Oct. 16, 2019, pp. 1-8. |
| Office Communication for U.S. Appl. No. 16/165,631 dated Oct. 8, 2019, pp. 1-4. |
| Office Communication for U.S. Appl. No. 16/114,139 dated Sep. 9, 2019, pp. 1-2. |
| Office Communication for U.S. Appl. No. 16/384,761 dated Nov. 29, 2019, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/976,269 dated Oct. 8, 2019, pp. 1-2. |
| Office Communication for U.S. Appl. No. 16/165,631 dated Dec. 27, 2019, pp. 1-6. |
| Office Communication for U.S. Appl. No. 16/679,110 dated Feb. 13, 2020, pp. 1-9. |
| Office Communication for U.S. Appl. No. 16/435,392 dated Feb. 21, 2020, pp. 1-9. |
| Office Communication for U.S. Appl. No. 16/659,513 dated Mar. 20, 2020, pp. 1-12. |
| Office Communication for Chinese Patent Application No. 201780018948.1 dated Mar. 27, 2020, pp. 1-14. |
| Office Communication for U.S. Appl. No. 16/530,818 dated Apr. 6, 2020, pp. 1-5. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Apr. 9, 2020, pp. 1-5. |
| Office Communication for U.S. Appl. No. 17/189,204 dated Jan. 11, 2022, pp. 1-24. |
| Office Communication for Japanese Patent Application No. JP 2019-561820 dated Mar. 7, 2022, pp. 1-11. |
| Office Communication for U.S. Appl. No. 17/214,505 dated Mar. 16, 2022, pp. 1-12. |
| Office Communication for U.S. Appl. No. 15/953,278 dated May 2, 2022, pp. 1-10. |
| Office Communication for U.S. Appl. No. 17/189,204 dated May 2, 2022, pp. 1-14. |
| Office Communication for U.S. Appl. No. 16/790,592 dated May 19, 2022, pp. 1-10. |
| Office Communication for U.S. Appl. No. 17/187,069 dated Jun. 28, 2023, pp. 1-11. |
| Office Communication for U.S. Appl. No. 15/953,278 dated Jul. 6, 2023, pp. 1-5. |
| Number | Date | Country | |
|---|---|---|---|
| 20220326594 A1 | Oct 2022 | US |
| Number | Date | Country | |
|---|---|---|---|
| 63100040 | Feb 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 17189204 | Mar 2021 | US |
| Child | 17850102 | US |
