Scene change detection in a dimensioner

Description

FIELD OF THE INVENTION

The present invention relates to a dimensioner device that uses image processing to measure the physical size of an object. More particularly, a method and apparatus is provided for determining if a scene has changed indicating respective movement between a camera and a measurement platform.

BACKGROUND

A fixed-position package dimensioner is used to measure the X, Y and Z dimensions of an object such as a package. To provide accuracy, such a dimensioner assumes a static relationship between a camera and a plane upon which objects such as parcels are placed. Once this relationship is established, translation or rotation of the camera will usually lead to under/over estimates of a parcel's size. Likewise, the reference plane (e.g., a scale or platform) against which the dimensioner measures packages cannot usually move without introducing error. In other words, the sensors and reference plane should not move relative to each other after initialization. Independent movement of parts within the system can lead to poor accuracy of measurements of packages in all dimensions.

If a user intentionally moves the sensors to change the view of the scene, for example, previous knowledge about the reference plane becomes invalid. The user may not even be aware that changing a sensor's pose will invalidate the original setup and reduce measuring accuracy.

The user may also be unaware that the dimensioning system hardware has moved. Movement could be very gradual over time, due to, for example, a loose mounting bracket and vibration or jarring. A sensor on a wire or pole could slide slightly over time or be accidently bumped out of position.

Therefore, a need exists for an automated process of re-discovering a reference plane when initial alignment has been disturbed.

SUMMARY

Accordingly, in one aspect, the present invention embraces a package dimensioner. Change in the pose of the package dimensioner is detected by background modeling the area of a measurement platform and then determining if a number of points in a scene are different in distance from the background model. Change in the pose can also be detected by comparing a count of support points in a 3D container generated from images taken in a training process with a count of support points in a subsequent images and determining how many support points are different.

In an example embodiment, a method of detecting a change in the pose of a package dimensioning system relative to its operating environment involves: initializing the dimensioning system by: at a range camera, capturing one or more initial reference images of a measurement platform and surrounding area; at a processor: generating a reference depth map from each initial reference image; generating and storing to a memory a background model from the captured initial reference depth maps; testing the dimensioning system for a scene change by: at the range camera, capturing a subsequent image of the measurement platform and surrounding area; at the processor: generating a current depth map from the subsequent image; comparing each pixel of the current depth map with a corresponding pixel of the background model; counting a number of pixels Pv of the current depth map that differ absolutely from the reference depth map by more than the prescribed threshold THRESH1, and if the number of pixels Pv is greater than a threshold THRESH2, determining that a significant change in the image has occurred.

In another example embodiment, a dimensioning system has a measurement platform. A range camera is mounted so as to capture an image of the measurement platform and surrounding area. A processor is programmed to carry out the following actions: initialize the dimensioning system by: receiving one or more initial reference images of the measurement platform and surrounding area from the range camera; generating and storing to a memory a background model from the one or more captured initial reference images; test the dimensioning system for a scene change by: receiving a subsequent image of the platform area from the range camera; generating a current depth map from the subsequent image; comparing each pixel of the current depth map with a corresponding pixel of the background model; counting a number of pixels Pv of the current depth map that differ absolutely from the reference depth map by more than the prescribed threshold THRESH1, and if the number of pixels Pv is greater than a threshold THRESH2, determining that a significant change in the image has occurred.

In certain illustrative embodiments, the testing is carried out on a periodic basis. In certain illustrative embodiments, the process further involves 9. The system according to claim 7, further comprising the processor executing a dimensioning process to measure dimensions of an object on the measurement platform. In certain illustrative embodiments, the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform. In certain illustrative embodiments, the testing is carried out prior to each measurement of dimensions of an object on the measurement platform. In certain illustrative embodiments, the processor generates an alert upon determining that a significant scene change has occurred. In certain illustrative embodiments, upon determining that a significant scene change has occurred, the processor repeats the initializing.

In another example embodiment, a method of detecting a change in the pose of a package dimensioning system relative to its operating environment involves: initializing the dimensioning system by: at a range camera, capturing an initial reference image of a measurement platform and surrounding area; at a processor, generating a three-dimensional container around the platform and storing the container to memory; at the processor, determining a count of the support points in the container from the reference image; testing the dimensioning system for a scene change by: at the range camera, capturing a subsequent image of the measurement platform and surrounding area; at the processor: counting support points in the subsequent image that are in the container; comparing the count of support points in the container in the subsequent image with the count of support points in the container in the reference image; based on the comparison, determining if a prescribed difference in the counts is present. Determining that a prescribed difference in the counts exists which establishes that a significant scene change has occurred.

In certain illustrative embodiments, the testing is carried out on a periodic basis. In certain illustrative embodiments, the process further involves executing a dimensioning process to measure dimensions of an object on the platform. In certain illustrative embodiments, the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform. In certain illustrative embodiments, the testing is carried out prior to each measurement of dimensions of an object on the measurement platform. In certain illustrative embodiments, the process further involves generating an alert upon determining that a significant scene change has occurred. In certain illustrative embodiments, the container comprises a right prism with a base approximating a convex polygon, where the base is parallel to a congruent convex polygon that bounds the measurement platform, and where the prism's height equals twice a maximum support distance. In certain illustrative embodiments, the container comprises a right cylinder with a circular base, where the base is parallel to a congruent circle that bounds the measurement platform, and where the cylinder's height equals twice the maximum support distance. In certain illustrative embodiments, when a significant scene change is deemed to have occurred, searching the scene for the measurement platform at a location coplanar therewith. In certain illustrative embodiments, upon determining that a significant scene change has occurred, the process involves repeating the initializing.

In a further example embodiment, a dimensioning system has: a measurement platform. A range camera is mounted so as to capture an image of the measurement platform and surrounding area. A processor is programmed to carry out the following actions: initialize the dimensioning system by: receiving an initial reference image of a platform area from the range camera; generating a three-dimensional container around the measurement platform and storing the container to memory; determining a count of the support points in the container from the reference image; test the dimensioning system for a scene change by: receiving a subsequent image of the measurement platform and surrounding area from the range camera; counting support points in the subsequent image that are in the container; comparing the count of support points in the container in the subsequent image with the count of support points in the container in the reference image; based on the comparison, determining if a prescribed difference in the counts of support points is present; and upon determining that a prescribed difference in the counts exists which establishes that a significant scene change has occurred.

In certain illustrative embodiments, the testing is carried out on a periodic basis. In certain illustrative embodiments, the process further involves executing a dimensioning process to measure dimensions of an object on the measurement platform. In certain illustrative embodiments, the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform. In certain illustrative embodiments, the testing is carried out prior to each measurement of dimensions of an object on the measurement platform. In certain illustrative embodiments, the process further involves generating an alert upon determining that a significant scene change has occurred. In certain illustrative embodiments, the container comprises a right prism with a base approximating a convex polygon, where the base is parallel to a congruent convex polygon that bounds the measurement platform, and where the prism's height equals twice the maximum support distance. In certain illustrative embodiments, the container comprises a right cylinder with a circular base, where the base is parallel to a congruent circle that bounds the measurement platform, and where the cylinder's height equals twice the maximum support distance. In certain illustrative embodiments, when a significant scene change is deemed to have occurred, searching the scene for the measurement platform at a location coplanar therewith. In certain illustrative embodiments, when a significant scene change has been established to have occurred, the processor further repeats the initialization.

The foregoing illustrative summary, as well as other exemplary objectives and/or advantages of the invention, and the manner in which the same are accomplished, are further explained within the following detailed description and its accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example of a dimensioner arrangement consistent with certain example embodiments.

FIG. 2 depicts an example range camera configuration consistent with certain example embodiments.

FIG. 3 is an example of a flow chart of a process that uses a background model to determine if a scene change has taken place in a manner consistent with certain embodiments.

FIG. 4 is a further example of a flow chart of a process that uses a background model to determine if a scene change has taken place in a manner consistent with certain embodiments.

FIG. 5 is an example of a flow chart of a process that uses a prism constructed about a polygon to determine if a scene change has taken place in a manner consistent with certain embodiments.

FIG. 6 depicts an example of construction of a prism about a polygon in a manner consistent with certain embodiments.

FIG. 7 is a further example of a flow chart of a process that uses a prism constructed about a polygon to determine if a scene change has taken place in a manner consistent with certain embodiments.

DETAILED DESCRIPTION

The embodiments consistent with the present invention embrace several methods and apparatus for detecting that a dimensioner is out of alignment by virtue of movement of a component of the system with respect to other components of the system.

For purposes of this document, the term “Mixture of Gaussians” refers to methods of background modeling. Single-channel grayscale images, RGB images, or depth images could be used (depth images contain Z-values observed at each pixel location). Each pixel location has one or more associated Gaussian (Normal) probability distributions (Gaussians) based on the observed intensities. The multiple Gaussians are mixed together to form joint distributions. The Gaussians can be dynamic; new ones can be added, or they could merge, or the mean (mu) and standard deviation (sigma) can change.

The term “support points” means three dimensional (XYZ) points that contribute to the definition of some geometric shape. Support points for a plane are points in 3D space detected by the system which are very close (in distance) to a reference plane. A threshold distance (for example, a few centimeters) defines how close a point must be to the geometric surface for the point to be considered supporting point. A three dimensional support point in the scene contributes to the equation for a three dimensional reference plane. The point “supports” the reference plane in that the point is relatively close to the reference plane and is used in fitting the plane (i.e., determining a location of the reference plane in 3D space). For purposes of this document, a support point is within a threshold absolute distance from the plane, such as a maximum of e.g., 2 cm. away orthogonally. Also, the approximated surface normal at the support point is near the surface normal of the platform's plane (with a maximum threshold angle of for example a few degrees between 3D normal vectors). A support point approximates a true point somewhere on the plane, but due to noise, the support point may be slightly above or below the true plane of the reference plane.

In one embodiment, the processor may use a combination of RANSAC (random sample consensus) and least squares fitting to find a three-dimensional plane that approximates the platform's top surface. In RANSAC, the processor builds a large number of random planes and outputs the plane with the largest number of support points. In each iteration of RANSAC, the processor chooses three three-dimensional points randomly from the set of points in the scene and constructs a plane through the points. The processor then counts the number of support points from the scene that are near the plane within a threshold distance. Finally, given the plane with the largest number of support points and the list of support points, the processor fits a new plane through the support points using least squares.

The term “convex hull” means a mathematically constructed polygon in three dimensional space that describes the outermost extent of the platform/scale. By “convex,” the polygon doesn't have any “dents” where successive vertices change from a counter-clockwise to a clockwise orientation or vice-versa. The convex hull generally has a small number of vertices, all of which are coplanar in 3D.

The term “platform” or “measurement platform” is used to mean a reference plane for dimensioning such as a floor or table/counter top surface or a weight scale top surface.

The term “prism” is used to mean a mathematically constructed structure that uses shifted copies of the convex hull as bases. The convex hull is shifted up along the platform's normal vector to form the top base, and the convex hull is shifted down in the opposite direction of the platform's normal vector to form the lower base. The height of the prism is often only a few centimeters and is meant to contain the support points near the actual platform. In this manner, walls are mathematically constructed normal to the convex hull to define a space bordered by the platform. In this document, the prism can essentially be considered a bounding container (a mathematical construct—not an actual physical container) around the platform. The container could be a “right prism” with bases that are polygons and segments representing height that are perpendicular to the bases. Or, the container could be a “right cylinder” with circular or elliptical bases. In all cases, the prism represents a shell around a polygon representing the platform that is flat in 3D space. A height (e.g., +/−2 cm) is added to form the prism or cylinder.

In accord with certain embodiments a mechanism is provided to detect when a camera forming a part of a dimensioning system has moved—perhaps even by a small amount—and alert the user and/or shut down dimensioning operations until a re-initialization is completed to account for the movement. In the present document, “movement” means that the camera or platform is moved with respect to one another such that the image registered to the camera is changed from that image used in the initialization of the dimensioning system.

Further, minor changes in the scene that are not problematic should preferably be ignored if they do not significantly disturb the sensor-platform pose. For instance, if a user places a very large package in the scene that consumes most of a sensor's view, the system should not generate an alarm for a significant, global change. Correspondingly, the detection module should avoid false alarms in order not to annoy the user or to render the system unusable for its intended purpose.

Movement of components in a dimensioner system can be inhibited by incorporating physical restraints (to prevent motion of the camera with respect to the platform). Also, paper seals can be used to provide an indication of when such motion has taken place. But, additional physical sealing may unnecessarily increase product cost, and may need to be customized for conformity with local metrological certification rules. Relative to this, an algorithmic approach does not add to the hardware cost and is consistent with the certification rules in that it renders the system inoperable when it is unable to produce an accurate result. Of course, physical restraints and seals can also be used in conjunction with the techniques disclosed herein.

Turning now to FIG. 1, a dimensioner system 10 is depicted in which a camera 14 is mounted in a fixed relationship to a measurement platform (“platform”) upon which parcels or other objects such as 22 to be measured are placed. The parcel 22 may be placed on a weight scale 24 positioned on the table top 18 so that weight can be determined at the same time as the overall dimensions in X, Y and Z directions are determined for the parcel being measured. In this instance, the top surface of the weight scale 24 becomes the reference plane or platform from which the dimensions are referenced. The dimension determinations are made by analysis of the images from camera 14 by a programmed processor 26 and associated memory/storage 28 (e.g., RAM, ROM, volatile and non-volatile memory and/or disc drives or flash memory, etc.) which ultimately can display the size to a display 30 forming part of a user interface for the system.

A range camera 14 such as that depicted in FIG. 2 is used in accord with certain example embodiments. Such a range camera 14 generates 3D spatial data. The camera 14 (or the camera 14 in conjunction with processor 26) provides 3D spatial data from which the processor 26 infers the reference plane. Camera 14, in certain implementations, includes an infrared (IR) camera 34 and an RGB camera 38 in a stereoscopic arrangement as shown with a horizontal spacing between the lens/aperture of the two cameras. The camera 14 further incorporates an infrared projector 42 which projects structured light using a laser and diffractive optical element(s) to produce a large number (e.g., about 50,000 to 100,000, for certain example embodiments) of 3D reference points in certain embodiments. While shown as part of camera 14, the projector can be a separate component without limitation.

Range cameras such as 14 are commercially available or can be custom built. It is desirable for enhancement of accuracy for the range camera to have a wide viewing angle and be able to focus on the objects that are being measured (e.g., within about 0.5 to 4.0 meters in certain example embodiments). It is also desirable for the camera to have a large baseline D (e.g., between about 8 and about 25 cm), since larger baselines will produce greater accuracy.

In each case of the present system, when the system is turned on an “initialization phase” starts the process. During the initialization phase, the user selects a platform (e.g., a scale). This can be done by presenting an image from the RGB camera 38 of camera 14 and requesting the user to indicate a location on the platform, e.g. by clicking a mouse when the pointer is on the platform or tapping the platform on a touch-screen display. Other methods may occur to those skilled in the art upon consideration of the present teachings.

Two separate example methods for detecting a moved sensor and/or platform are provided by way of example herein, but the invention itself is not to be constrained by the details of the techniques disclosed. In each case, when it is established that a significant scene change has occurred, any number of actions can be carried out including, but not limited to providing an audible or visual alert to the user and/or repeating the initialization phase to account for the change in pose.

Background Model Example

In one implementation, background modeling is used to detect a changed scene. In the background model example, the system prompts the user to select the platform during initialization phase. The depth maps are used to train a background model. While testing a new scene, the already captured background model is compared to a depth map of a current image. Such a depth map may contain information for 100,000 pixels in one example. The system then classifies the pixels in the image as foreground if the depth value for that pixel is significantly different from the corresponding depth of the trained background model. If most of the test scene is classified as foreground, then the system determines that the camera or platform has been moved (or that there has otherwise been a significant scene change).

Once movement of camera or platform is detected, the system acquires a new platform location. The system finds the new location of platform by searching for the largest plane that is coincident with the previous plane as defined by a planar equation of the platform. The planar parameters can then be adjusted according to the newly obtained location. In addition, the system may wait for a fixed amount of time before alerting the user regarding any relative movement between the camera and the platform so as to avoid false alerts.

If the relative position of the camera and platform changes significantly, the camera's current images should vary significantly from images captured during an initialization phase of operation of the system. FIG. 3 depicts an example flow chart of a process 100 consistent with an example implementation starting at 104 where the device is started or restarted and initialized. The user is prompted to select the desired platform at 108 and the system finds the platform at 112. The user can then approve this platform at 116.

The system captures, via camera 14, at least one depth map containing depth (or Z-values in X,Y,Z geometry) in a regular matrix (forming a range image). The depth map(s) is used to train a background model at 120 by generating per-pixel statistical (e.g., Gaussian) distributions consistent with the captured depth map for a collection of successive captured images from camera 14. This trained background model represents a depth map of the environment of the platform as the platform appeared at the time when the system was trained at 120.

Training the background model involves an initial training phase of a blank scene and then continual updates, even when testing. Generally, the background model of an empty scene (containing the platform but no parcel) is trained for e.g., 5 to 10 minutes at startup. Then, during testing, the processor will find foreground objects that violate the background model and will also adapt/update the model. The initial training and update phases essentially make similar changes to the background model, but the update phase ignores foreground ‘blobs’ and doesn't update the model for points where foreground was detected.

Initial training of the background model is carried out by placing the camera in a fixed position, such as on a tripod or a rigid mount. A plurality of frames is obtained from the camera for at least about 30 seconds. The scene should contain minimal disruptions like people walking through it. Then, one of the following processes is carried out for each frame:

1) Assuming use of depth maps (a regular matrix of depth values for each pixel), the frame will be a regular matrix with a depth value (e.g., expressed in mm) or disparity value at each pixel location.

2) Assuming use of a “mixture of Gaussians” model, each training frame is used to update a Gaussian model for each pixel location. Distributions could merge together, or new ones can be created. The mean and standard deviation is then updated for each Gaussian model for each pixel.

Once the background model is trained at 120, the system can begin operation to measure objects placed upon the platform (or placed upon a scale on the platform) in a dimensioning loop 124.

It is desirable to frequently check the alignment of the system to assure that the camera to platform orientation (the “pose”) has not changed. This is done in a “testing phase”. In certain example embodiments, this is checked at three different instances. A check can be done 1) prior to each parcel measurement, 2) after a periodic downtime has been reached (i.e., time between measurements), and 3) on a strictly periodic basis. Many variations will occur to those skilled in the art upon consideration of the present teachings.

During the testing phase, at each test frame, the background model is updated, skipping updates for foreground regions. Just as in the initialization phase, the statistics (e.g., the Gaussians) can be updated. Foreground objects left stationary for a long time will eventually become background as a result of these updates. The example system uses a maximum number of old frames that are stored as history and older frames are eventually deleted. For certain example implementations, the system “forgets” frames that were captured more than about 10,000 frames ago. In one example system, frames are captured at about 10 frames per second.

In the present example embodiment, at 128 a downtime timer Td is set prior to the first measurement along with a periodic timer Tp as indicated at 128. At 132, a new frame is received from camera 14. At 134, the user can start a new measurement by initiating a command to the user interface 30 at 136. When this happens, the system first runs a check (by going into a testing phase) to assure that there has been no movement to disturb alignment of the system. This occurs at 140 and 144 where the system checks to see if a large number (as defined by a threshold) of variations are present from the background model trained at 120. A first threshold THRESH1 defines the maximum distance between the current value of a pixel's depth and the value in the background model. The distance in this case is unsigned since it is of no concern about whether the distance is closer or farther from the camera, the only thing of relevance is how far away the depth is from the corresponding depth in the background model. Thus, if a pixel's depth value differs from the background model by a distance greater than THRESH1, the variation is deemed to be large enough to be considered a variation from the background model. The number of such variations are counted to produce a count PV and PV is compared to a second threshold THRESH2 to determine if there is great enough variation to judge that there has been a change in the “pose” of the system.

When carrying out this test at 140 and 144, the current depth map is compared to the depth map representing the background model. The system classifies a pixel as foreground if its depth value differs from the trained value by more than THRESH1 (for example if the difference is greater than about 5-20 mm in one example). If a large amount of the current depth map is classified as foreground points (e.g., if the number of points Pv is greater than THRESH2), then it can be concluded that the camera probably moved or the alignment of the system otherwise changed. Thus, at 144, the number of foreground points Pf is compared to a threshold THRESH2 to determine if there has been movement or not if the number of foreground points is greater than THRESH2. In one illustrative example, the value of THRESH2 can be set at about 75-95% of the total number of points.

Using depth maps in background modeling is a method that is robust against shadows and other lighting changes. It is noted that RGB/gray images can also be used in a background model. In addition, the background models of this example are not adaptive, but could be modified to adapt them to accept long-term changes, like a newly introduced, semi-permanent object, into the background model.

If, at 144, the system determines that the threshold THRESH2 has not been exceeded and the system has not been moved, the user can be prompted to place a parcel or other object to be measured on the platform at 148. The package can then be measured by the system at 152 and the results displayed or otherwise used (e.g., as input to a point of sale system) at 156 and the downtime timer Td is reset at 160.

If the user is between measurements and has not generated an instruction indicating that the measurement is to start at 138 for a time Td (e.g., for example 15 to 30 minutes), the process 100 goes to 164 to check to see if the downtime timer Td has expired. If Td has not expired, the process returns to 132 to await the next frame from the camera. If Td has expired, the timer Td is reset at 168 and a process identical to that defined at 140 and 144 is started at 172 and 176 to assure that the system is in alignment. At 144 or 176, if the process detects that there has been a camera movement or other change that affects alignment, the process generates an alert at 180 to make the user aware that the system is out of alignment and that an alignment initialization process is to be initiated. This alert can be an audible or visual alert that is intended to get the user's attention. The process then returns to an earlier point in the process such as 108 to begin an alignment re-initialization of the system.

In addition to the downtime timer, a periodic timer can be used to check the calibration on a regular basis (e.g., for example every 15 minutes). If the timer Tp has not expired at 164, the system checks to see if the periodic timer Tp has expired at 184. If not, the process awaits a new frame from the camera 14 at 132. If timer Tp has expired, the periodic timer Tp is reset at 188 and control passes to 172.

FIG. 4 shows a somewhat more isolated and detailed example of a process 200, such as that carried in process 100, starting at an initialization phase 202 where the Z direction values are captured as a depth map matrix. This depth map is used at 206 to train a background model that establishes which points are considered background.

At 210, a test of the current scene is initiated in which a new depth map is created for the current scene. This new depth map is compared with the trained background model (i.e., a reference depth map created at the time of initialization of the system). At 214, each pixel of the new depth map is compared to the corresponding pixel of the trained background model and if the value differs greatly (for example, if the pixel differs by more than THRESH1), then the new pixel is classified as a foreground pixel 218. Otherwise, the pixel will be classified as a background pixel 222. The number of foreground points and background points Pv are counted at 226 and the number of foreground points is compared to a threshold THRESH2 at 230. If the number of foreground points is greater than THRESH2, then the system deems that a change (movement) has been detected at 234 and a new initialization and training process is initiated. If no movement is detected at 238, the system is deemed to be in condition to make dimensioning measurements. In example embodiments, the values of THRESH1 and THRESH2 can likely be optimized for any given dimensioning setup and system. Many variations will occur to those skilled in the art upon consideration of the present teachings.

When background modeling is used for the present system, a few possible models can be considered. A single range image from range camera 14 can be used for the model and the process can determine the difference between the test image and the trained reference images to find foreground. When using one range image for the background model, in one implementation, a distance threshold THRESH1 of 5 mm and a threshold foreground percentage THRESH 2 of 90% can be used. In other words, any new depth value that differs from the corresponding trained depth value by more than a threshold (e.g., 5 mm in one example) is deemed foreground, and if more than 90% of pixels are foreground in one example, then the camera or platform is deemed to have moved.

In another example, a single Gaussian at each pixel location can be used and trained with perhaps a few minutes (e.g., 1-5 minutes) of frames of a blank scene. Each pixel has one Normal distribution of depths with a mean value and standard deviation value. When testing, standard Z values can be computed over the scene. Absolute Z-values surpassing some threshold, like for example three standard deviations, could be deemed foreground. Many variations are possible without deviating from the principles described herein.

Complex Hull Example

In another implementation, referred to as the complex hull method, the dimensioning system 10 checks to determine whether or not the platform remains in the location where it was first imaged by use of a complex hull as defined above.

In this example, the system prompts the user to select the platform during initialization phase in the same manner previously described. Then, a convex hull is built around the selected platform. The convex hull contains the supporting points for the platform. While testing a new scene, the quantity of support points within a prism or cylinder is calculated using the original platform's convex hull as a reference end of the prism or cylinder. If too few or too many of the support points exist in the hull, then the system concludes that the platform or the camera has been moved. Further, the system waits for a fixed amount of time (e.g., 5 seconds), to raise an alarm upon detection of relative movement between camera and platform. Once the movement of camera or platform is detected, the system acquires the new platform location. The system finds the new location of the platform by searching for the largest plane that is approximately coincident with the previous planar equation of the platform and adjusts the planar parameters according to the newly obtained location.

A process 300 representing this example implementation is depicted in FIG. 5. The process starts at 304 with startup or reset of the dimensioning system 10. At 308, the user selects the desired platform to be used for the dimensioning. This can be done by presenting an image from the RGB camera 38 of camera 14 and requesting the user to indicate a location on the platform, e.g. by clicking a mouse when the pointer is on the platform or tapping the platform on a touch-screen display. Other methods may occur to those skilled in the art upon consideration of the present teachings.

During the initialization phase at 312, the platform is found in an initial image captured by camera 14. The processor 26 then computes a “convex hull” around the platform. This convex hull should contain support points for the platform (as defined above). As explained above, the convex hull is essentially a polygon in three dimensions, but which is approximately coincident with the reference plane of the platform.

FIG. 6 depicts the process of constructing walls of a prism about the complex hull. The complex hull 312 in this simple example case is a four sided parallelogram 311. But, in other examples, the complex hull could be represented by a polygon that has three or more sides (or a cylinder or oval) and is used to characterize the surface of the platform that serves as a reference plane. In this illustration, a plurality of support points is shown in the complex hull 311. While these support points are shown to be on the plane of the complex hull, they may differ slightly from actual coplanar points (e.g., points 313). The prism can be constructed mathematically by extending walls 314, 316, 318 and 320 upwards in a direction normal to the complex hull toward a projection of the complex hull that forms a parallel plane to the complex hull.

When the prism has been defined by the system at 312, the user may be prompted to approve the identified platform at 324 and if the user does not approve, he or she again selects the platform at 308 and the complex hull is again identified and the prism walls constructed at 312.

Once the user approves the proper selection of the platform at 324, the system is ready to carry out the dimensioning process which operates as a continuous loop at 328. As in the prior example, this example is shown to have three separate timing arrangements to do a scene change test upon the dimensioning system. To accomplish this, timers Tp and Td are set at 332 and a new frame is received from camera 14 at 336.

The user can start a new measurement at 340 to dimension a parcel or other object. But until such measurement is initiated at 340, the system checks the status of the downtime timer Td at 342. If Td has not expired at 342, the periodic timer Tp is checked at 344. If Tp has not expired, the process returns to 336. If the downtime timer Td has expired at 342 it is reset at 348 and control passes to 350. Similarly, if the periodic timer Tp has expired at 344, it is reset at 352 and control passes to 350. In either case, at 350, the number of points is counted in the prism and if this number differs significantly from the count obtained from the originally established trained reference prism, a significant scene change will be deemed to have occurred. This determination is made at 354 where the system determines if the count is within a suitable range based on a computation at 350 which determines a ratio R of the reference count to the current count. This reference can be deemed to represent no significant change if the value of this ratio (Pv) is between a lower acceptable ratio and a higher acceptable ratio (e.g., for example 0.8<Pv<1.25). If Pv is within this range at 354, no movement is deemed to have taken place and the process returns to 336. But, if the value of Pv is outside this range at 354, a significant scene change is deemed to have occurred and an alert is issued at 358 to the user so that the system can be reinitialized starting at 308.

Whenever a user wishes to measure a parcel or other object at 340 and initiates such process, another initial check is carried out starting at 362 which carries out the same process as 350. A decision is made at 366 whether or not Pv is within range and if not, control passes to 358 to alert the user and re-initialize the system. If no scene change is detected (no movement) at 366, the user is prompted to place the object on the platform at 370 and the parcel is measured at 374. Results can be displayed at 378 or other appropriate action (e.g., transferring data to a point of sale terminal or other system) and the downtime timer is reset at 382. Control then passes back to 336.

When testing the current scene, support points are identified near the original plane (e.g., within a few mm) according to the planar equation that defines the complex hull. The quantity of support points within the “prism” is counted using the original platform's convex hull as a base. If many support points are found to still exist in the convex hull, then the platform and/or camera can be deemed to have not moved. Otherwise, the user can be alerted of a changed pose in the dimensioning system. Once relative movement between the camera and platform is detected, the user is directed to re-find the platform. The old platform is invalid, so the process of reporting dimensions of packages is immediately halted.

In one implementation, the process attempts to reacquire the platform as discussed above. Reacquisition assumes the original planar equation is still valid, but the platform has simply moved with the same plane. For example, a user may move a scale to another location on a countertop, but the scale's planar equation is still valid, so the process can try to find the new location of the scale. In one method, the process finds the largest plane that is approximately coincident with the previous plane, and it ensures the new quantity of support points is similar (e.g., within a threshold) to the original count. The process can then appropriately adjust the planar parameters.

Downtime can be established by determining if the user has not measured anything in X seconds. Likewise, if an RGB frame of the scene has not changed significantly in X seconds, the system could run check. It is desirable to find downtimes when the user is not actively measuring so that the integrity of the alignment can be confirmed with minimal disturbance of the user's operation of the dimensioner.

Referring now to FIG. 7, a process 400 consistent with the discussion above is depicted starting at an initialization phase at 404. During this initialization phase, the polygon defining the complex hull that contains support points is used as the base to construct the prism walls. At 408, once the system is initialized, the current scene is tested by finding support points that are near (e.g., within about 10-30 mm) of the original support points. At 412, the number of support points within the prism is counted using the original platform polygon as the base. At 416, a ratio R of counts is taken (the current count divided by the original count) and this ratio R is compared to a lower threshold (THRESH-LOW) and an upper threshold (THRESH-HIGH) and if the ratio is between the lower and higher thresholds the system deems that there has been no significant change in the scene at 420 (e.g., no movement of the camera with respect to the platform). In such case, normal dimensioning can be carried out. However, if the ratio R is outside this range, the system deems that a significant scene change has taken place (e.g., there has been movement of the camera with respect to the platform) at 424. In such case, an alarm or other alert can be generated to make the user aware of the situation and/or a new initialization process can be initiated as previously discussed.

It is noted that the lower and upper thresholds can be adjusted and optimized so as to establish how much change can be tolerated within the bounds of what would be considered significant and cause to halt measurements until a re-initialization can be carried out. Changes in lighting, movement within the camera's view (e.g., hands passing over the platform, etc.) can contribute to noise that is accounted for in part by the range between the thresholds.

In the implementation of finding support points for the original planar equation, a small point-to-plane distance threshold was used. For instance, a point may be deemed to exist in the original plane's support if its distance from the plane is less than about 20 mm. The corresponding convex prism is short in height, perhaps having a height of as much as about twice this maximum distance (i.e., 2*20=40 mm).

In certain implementations, a countdown timer can be used for concluding that the camera actually moved. The system should observe a significantly changed scene for X seconds before concluding that the camera/platform changed pose. After the countdown expires, the process changes to the phase of requiring the user to select the reference plane again. This countdown helps to further prevent false alarms and by calling for a sustained change to the scene before producing a “camera moved” alarm. For example, a user may place a large package in the scene that violates the background model, but if he/she removes it before the countdown expires, then the system will not throw an alarm. In practice, a countdown of several minutes (e.g., 5-10 minutes) was found to be appropriate to provide a good balance between false alarms and accurate dimensioning. Many variations and modifications will occur to those skilled in the art upon consideration of the present teachings.

To supplement the present disclosure, this application incorporates entirely by reference the following commonly assigned patents, patent application publications, and patent applications:

U.S. Pat. No. 6,832,725; U.S. Pat. No. 7,128,266;
U.S. Pat. No. 7,159,783; U.S. Pat. No. 7,413,127;
U.S. Pat. No. 7,726,575; U.S. Pat. No. 8,294,969;
U.S. Pat. No. 8,317,105; U.S. Pat. No. 8,322,622;
U.S. Pat. No. 8,366,005; U.S. Pat. No. 8,371,507;
U.S. Pat. No. 8,376,233; U.S. Pat. No. 8,381,979;
U.S. Pat. No. 8,390,909; U.S. Pat. No. 8,408,464;
U.S. Pat. No. 8,408,468; U.S. Pat. No. 8,408,469;
U.S. Pat. No. 8,424,768; U.S. Pat. No. 8,448,863;
U.S. Pat. No. 8,457,013; U.S. Pat. No. 8,459,557;
U.S. Pat. No. 8,469,272; U.S. Pat. No. 8,474,712;
U.S. Pat. No. 8,479,992; U.S. Pat. No. 8,490,877;
U.S. Pat. No. 8,517,271; U.S. Pat. No. 8,523,076;
U.S. Pat. No. 8,528,818; U.S. Pat. No. 8,544,737;
U.S. Pat. No. 8,548,242; U.S. Pat. No. 8,548,420;
U.S. Pat. No. 8,550,335; U.S. Pat. No. 8,550,354;
U.S. Pat. No. 8,550,357; U.S. Pat. No. 8,556,174;
U.S. Pat. No. 8,556,176; U.S. Pat. No. 8,556,177;
U.S. Pat. No. 8,559,767; U.S. Pat. No. 8,599,957;
U.S. Pat. No. 8,561,895; U.S. Pat. No. 8,561,903;
U.S. Pat. No. 8,561,905; U.S. Pat. No. 8,565,107;
U.S. Pat. No. 8,571,307; U.S. Pat. No. 8,579,200;
U.S. Pat. No. 8,583,924; U.S. Pat. No. 8,584,945;
U.S. Pat. No. 8,587,595; U.S. Pat. No. 8,587,697;
U.S. Pat. No. 8,588,869; U.S. Pat. No. 8,590,789;
U.S. Pat. No. 8,596,539; U.S. Pat. No. 8,596,542;
U.S. Pat. No. 8,596,543; U.S. Pat. No. 8,599,271;
U.S. Pat. No. 8,599,957; U.S. Pat. No. 8,600,158;
U.S. Pat. No. 8,600,167; U.S. Pat. No. 8,602,309;
U.S. Pat. No. 8,608,053; U.S. Pat. No. 8,608,071;
U.S. Pat. No. 8,611,309; U.S. Pat. No. 8,615,487;
U.S. Pat. No. 8,616,454; U.S. Pat. No. 8,621,123;
U.S. Pat. No. 8,622,303; U.S. Pat. No. 8,628,013;
U.S. Pat. No. 8,628,015; U.S. Pat. No. 8,628,016;
U.S. Pat. No. 8,629,926; U.S. Pat. No. 8,630,491;
U.S. Pat. No. 8,635,309; U.S. Pat. No. 8,636,200;
U.S. Pat. No. 8,636,212; U.S. Pat. No. 8,636,215;
U.S. Pat. No. 8,636,224; U.S. Pat. No. 8,638,806;
U.S. Pat. No. 8,640,958; U.S. Pat. No. 8,640,960;
U.S. Pat. No. 8,643,717; U.S. Pat. No. 8,646,692;
U.S. Pat. No. 8,646,694; U.S. Pat. No. 8,657,200;
U.S. Pat. No. 8,659,397; U.S. Pat. No. 8,668,149;
U.S. Pat. No. 8,678,285; U.S. Pat. No. 8,678,286;
U.S. Pat. No. 8,682,077; U.S. Pat. No. 8,687,282;
U.S. Pat. No. 8,692,927; U.S. Pat. No. 8,695,880;
U.S. Pat. No. 8,698,949; U.S. Pat. No. 8,717,494;
U.S. Pat. No. 8,717,494; U.S. Pat. No. 8,720,783;
U.S. Pat. No. 8,723,804; U.S. Pat. No. 8,723,904;
U.S. Pat. No. 8,727,223; U.S. Pat. No. D702,237;
U.S. Pat. No. 8,740,082; U.S. Pat. No. 8,740,085;
U.S. Pat. No. 8,746,563; U.S. Pat. No. 8,750,445;
U.S. Pat. No. 8,752,766; U.S. Pat. No. 8,756,059;
U.S. Pat. No. 8,757,495; U.S. Pat. No. 8,760,563;
U.S. Pat. No. 8,763,909; U.S. Pat. No. 8,777,108;
U.S. Pat. No. 8,777,109; U.S. Pat. No. 8,779,898;
U.S. Pat. No. 8,781,520; U.S. Pat. No. 8,783,573;
U.S. Pat. No. 8,789,757; U.S. Pat. No. 8,789,758;
U.S. Pat. No. 8,789,759; U.S. Pat. No. 8,794,520;
U.S. Pat. No. 8,794,522; U.S. Pat. No. 8,794,525;
U.S. Pat. No. 8,794,526; U.S. Pat. No. 8,798,367;
U.S. Pat. No. 8,807,431; U.S. Pat. No. 8,807,432;
U.S. Pat. No. 8,820,630; U.S. Pat. No. 8,822,848;
U.S. Pat. No. 8,824,692; U.S. Pat. No. 8,824,696;
U.S. Pat. No. 8,842,849; U.S. Pat. No. 8,844,822;
U.S. Pat. No. 8,844,823; U.S. Pat. No. 8,849,019;
U.S. Pat. No. 8,851,383; U.S. Pat. No. 8,854,633;
U.S. Pat. No. 8,866,963; U.S. Pat. No. 8,868,421;
U.S. Pat. No. 8,868,519; U.S. Pat. No. 8,868,802;
U.S. Pat. No. 8,868,803; U.S. Pat. No. 8,870,074;
U.S. Pat. No. 8,879,639; U.S. Pat. No. 8,880,426;
U.S. Pat. No. 8,881,983; U.S. Pat. No. 8,881,987;
U.S. Pat. No. 8,903,172; U.S. Pat. No. 8,908,995;
U.S. Pat. No. 8,910,870; U.S. Pat. No. 8,910,875;
U.S. Pat. No. 8,914,290; U.S. Pat. No. 8,914,788;
U.S. Pat. No. 8,915,439; U.S. Pat. No. 8,915,444;
U.S. Pat. No. 8,916,789; U.S. Pat. No. 8,918,250;
U.S. Pat. No. 8,918,564; U.S. Pat. No. 8,925,818;
U.S. Pat. No. 8,939,374; U.S. Pat. No. 8,942,480;
U.S. Pat. No. 8,944,313; U.S. Pat. No. 8,944,327;
U.S. Pat. No. 8,944,332; U.S. Pat. No. 8,950,678;
U.S. Pat. No. 8,967,468; U.S. Pat. No. 8,971,346;
U.S. Pat. No. 8,976,030; U.S. Pat. No. 8,976,368;
U.S. Pat. No. 8,978,981; U.S. Pat. No. 8,978,983;
U.S. Pat. No. 8,978,984; U.S. Pat. No. 8,985,456;
U.S. Pat. No. 8,985,457; U.S. Pat. No. 8,985,459;
U.S. Pat. No. 8,985,461; U.S. Pat. No. 8,988,578;
U.S. Pat. No. 8,988,590; U.S. Pat. No. 8,991,704;
U.S. Pat. No. 8,996,194; U.S. Pat. No. 8,996,384;
U.S. Pat. No. 9,002,641; U.S. Pat. No. 9,007,368;
U.S. Pat. No. 9,010,641; U.S. Pat. No. 9,015,513;
U.S. Pat. No. 9,016,576; U.S. Pat. No. 9,022,288;
U.S. Pat. No. 9,030,964; U.S. Pat. No. 9,033,240;
U.S. Pat. No. 9,033,242; U.S. Pat. No. 9,036,054;
U.S. Pat. No. 9,037,344; U.S. Pat. No. 9,038,911;
U.S. Pat. No. 9,038,915; U.S. Pat. No. 9,047,098;
U.S. Pat. No. 9,047,359; U.S. Pat. No. 9,047,420;
U.S. Pat. No. 9,047,525; U.S. Pat. No. 9,047,531;
U.S. Pat. No. 9,053,055; U.S. Pat. No. 9,053,378;
U.S. Pat. No. 9,053,380; U.S. Pat. No. 9,058,526;
U.S. Pat. No. 9,064,165; U.S. Pat. No. 9,064,167;
U.S. Pat. No. 9,064,168; U.S. Pat. No. 9,064,254;
U.S. Pat. No. 9,066,032; U.S. Pat. No. 9,070,032;
U.S. Design Pat. No. D716,285;
U.S. Design Pat. No. D723,560;
U.S. Design Pat. No. D730,357;
U.S. Design Pat. No. D730,901;
U.S. Design Pat. No. D730,902;
U.S. Design Pat. No. D733,112;
U.S. Design Pat. No. D734,339;
International Publication No. 2013/163789;
International Publication No. 2013/173985;
International Publication No. 2014/019130;
International Publication No. 2014/110495;
U.S. Patent Application Publication No. 2008/0185432;
U.S. Patent Application Publication No. 2009/0134221;
U.S. Patent Application Publication No. 2010/0177080;
U.S. Patent Application Publication No. 2010/0177076;
U.S. Patent Application Publication No. 2010/0177707;
U.S. Patent Application Publication No. 2010/0177749;
U.S. Patent Application Publication No. 2010/0265880;
U.S. Patent Application Publication No. 2011/0202554;
U.S. Patent Application Publication No. 2012/0111946;
U.S. Patent Application Publication No. 2012/0168511;
U.S. Patent Application Publication No. 2012/0168512;
U.S. Patent Application Publication No. 2012/0193423;
U.S. Patent Application Publication No. 2012/0203647;
U.S. Patent Application Publication No. 2012/0223141;
U.S. Patent Application Publication No. 2012/0228382;
U.S. Patent Application Publication No. 2012/0248188;
U.S. Patent Application Publication No. 2013/0043312;
U.S. Patent Application Publication No. 2013/0082104;
U.S. Patent Application Publication No. 2013/0175341;
U.S. Patent Application Publication No. 2013/0175343;
U.S. Patent Application Publication No. 2013/0257744;
U.S. Patent Application Publication No. 2013/0257759;
U.S. Patent Application Publication No. 2013/0270346;
U.S. Patent Application Publication No. 2013/0287258;
U.S. Patent Application Publication No. 2013/0292475;
U.S. Patent Application Publication No. 2013/0292477;
U.S. Patent Application Publication No. 2013/0293539;
U.S. Patent Application Publication No. 2013/0293540;
U.S. Patent Application Publication No. 2013/0306728;
U.S. Patent Application Publication No. 2013/0306731;
U.S. Patent Application Publication No. 2013/0307964;
U.S. Patent Application Publication No. 2013/0308625;
U.S. Patent Application Publication No. 2013/0313324;
U.S. Patent Application Publication No. 2013/0313325;
U.S. Patent Application Publication No. 2013/0342717;
U.S. Patent Application Publication No. 2014/0001267;
U.S. Patent Application Publication No. 2014/0008439;
U.S. Patent Application Publication No. 2014/0025584;
U.S. Patent Application Publication No. 2014/0034734;
U.S. Patent Application Publication No. 2014/0036848;
U.S. Patent Application Publication No. 2014/0039693;
U.S. Patent Application Publication No. 2014/0042814;
U.S. Patent Application Publication No. 2014/0049120;
U.S. Patent Application Publication No. 2014/0049635;
U.S. Patent Application Publication No. 2014/0061306;
U.S. Patent Application Publication No. 2014/0063289;
U.S. Patent Application Publication No. 2014/0066136;
U.S. Patent Application Publication No. 2014/0067692;
U.S. Patent Application Publication No. 2014/0070005;
U.S. Patent Application Publication No. 2014/0071840;
U.S. Patent Application Publication No. 2014/0074746;
U.S. Patent Application Publication No. 2014/0076974;
U.S. Patent Application Publication No. 2014/0078341;
U.S. Patent Application Publication No. 2014/0078345;
U.S. Patent Application Publication No. 2014/0097249;
U.S. Patent Application Publication No. 2014/0098792;
U.S. Patent Application Publication No. 2014/0100813;
U.S. Patent Application Publication No. 2014/0103115;
U.S. Patent Application Publication No. 2014/0104413;
U.S. Patent Application Publication No. 2014/0104414;
U.S. Patent Application Publication No. 2014/0104416;
U.S. Patent Application Publication No. 2014/0104451;
U.S. Patent Application Publication No. 2014/0106594;
U.S. Patent Application Publication No. 2014/0106725;
U.S. Patent Application Publication No. 2014/0108010;
U.S. Patent Application Publication No. 2014/0108402;
U.S. Patent Application Publication No. 2014/0110485;
U.S. Patent Application Publication No. 2014/0114530;
U.S. Patent Application Publication No. 2014/0124577;
U.S. Patent Application Publication No. 2014/0124579;
U.S. Patent Application Publication No. 2014/0125842;
U.S. Patent Application Publication No. 2014/0125853;
U.S. Patent Application Publication No. 2014/0125999;
U.S. Patent Application Publication No. 2014/0129378;
U.S. Patent Application Publication No. 2014/0131438;
U.S. Patent Application Publication No. 2014/0131441;
U.S. Patent Application Publication No. 2014/0131443;
U.S. Patent Application Publication No. 2014/0131444;
U.S. Patent Application Publication No. 2014/0131445;
U.S. Patent Application Publication No. 2014/0131448;
U.S. Patent Application Publication No. 2014/0133379;
U.S. Patent Application Publication No. 2014/0136208;
U.S. Patent Application Publication No. 2014/0140585;
U.S. Patent Application Publication No. 2014/0151453;
U.S. Patent Application Publication No. 2014/0152882;
U.S. Patent Application Publication No. 2014/0158770;
U.S. Patent Application Publication No. 2014/0159869;
U.S. Patent Application Publication No. 2014/0166755;
U.S. Patent Application Publication No. 2014/0166759;
U.S. Patent Application Publication No. 2014/0168787;
U.S. Patent Application Publication No. 2014/0175165;
U.S. Patent Application Publication No. 2014/0175172;
U.S. Patent Application Publication No. 2014/0191644;
U.S. Patent Application Publication No. 2014/0191913;
U.S. Patent Application Publication No. 2014/0197238;
U.S. Patent Application Publication No. 2014/0197239;
U.S. Patent Application Publication No. 2014/0197304;
U.S. Patent Application Publication No. 2014/0214631;
U.S. Patent Application Publication No. 2014/0217166;
U.S. Patent Application Publication No. 2014/0217180;
U.S. Patent Application Publication No. 2014/0231500;
U.S. Patent Application Publication No. 2014/0232930;
U.S. Patent Application Publication No. 2014/0247315;
U.S. Patent Application Publication No. 2014/0263493;
U.S. Patent Application Publication No. 2014/0263645;
U.S. Patent Application Publication No. 2014/0267609;
U.S. Patent Application Publication No. 2014/0270196;
U.S. Patent Application Publication No. 2014/0270229;
U.S. Patent Application Publication No. 2014/0278387;
U.S. Patent Application Publication No. 2014/0278391;
U.S. Patent Application Publication No. 2014/0282210;
U.S. Patent Application Publication No. 2014/0284384;
U.S. Patent Application Publication No. 2014/0288933;
U.S. Patent Application Publication No. 2014/0297058;
U.S. Patent Application Publication No. 2014/0299665;
U.S. Patent Application Publication No. 2014/0312121;
U.S. Patent Application Publication No. 2014/0319220;
U.S. Patent Application Publication No. 2014/0319221;
U.S. Patent Application Publication No. 2014/0326787;
U.S. Patent Application Publication No. 2014/0332590;
U.S. Patent Application Publication No. 2014/0344943;
U.S. Patent Application Publication No. 2014/0346233;
U.S. Patent Application Publication No. 2014/0351317;
U.S. Patent Application Publication No. 2014/0353373;
U.S. Patent Application Publication No. 2014/0361073;
U.S. Patent Application Publication No. 2014/0361082;
U.S. Patent Application Publication No. 2014/0362184;
U.S. Patent Application Publication No. 2014/0363015;
U.S. Patent Application Publication No. 2014/0369511;
U.S. Patent Application Publication No. 2014/0374483;
U.S. Patent Application Publication No. 2014/0374485;
U.S. Patent Application Publication No. 2015/0001301;
U.S. Patent Application Publication No. 2015/0001304;
U.S. Patent Application Publication No. 2015/0003673;
U.S. Patent Application Publication No. 2015/0009338;
U.S. Patent Application Publication No. 2015/0009610;
U.S. Patent Application Publication No. 2015/0014416;
U.S. Patent Application Publication No. 2015/0021397;
U.S. Patent Application Publication No. 2015/0028102;
U.S. Patent Application Publication No. 2015/0028103;
U.S. Patent Application Publication No. 2015/0028104;
U.S. Patent Application Publication No. 2015/0029002;
U.S. Patent Application Publication No. 2015/0032709;
U.S. Patent Application Publication No. 2015/0039309;
U.S. Patent Application Publication No. 2015/0039878;
U.S. Patent Application Publication No. 2015/0040378;
U.S. Patent Application Publication No. 2015/0048168;
U.S. Patent Application Publication No. 2015/0049347;
U.S. Patent Application Publication No. 2015/0051992;
U.S. Patent Application Publication No. 2015/0053766;
U.S. Patent Application Publication No. 2015/0053768;
U.S. Patent Application Publication No. 2015/0053769;
U.S. Patent Application Publication No. 2015/0060544;
U.S. Patent Application Publication No. 2015/0062366;
U.S. Patent Application Publication No. 2015/0063215;
U.S. Patent Application Publication No. 2015/0063676;
U.S. Patent Application Publication No. 2015/0069130;
U.S. Patent Application Publication No. 2015/0071819;
U.S. Patent Application Publication No. 2015/0083800;
U.S. Patent Application Publication No. 2015/0086114;
U.S. Patent Application Publication No. 2015/0088522;
U.S. Patent Application Publication No. 2015/0096872;
U.S. Patent Application Publication No. 2015/0099557;
U.S. Patent Application Publication No. 2015/0100196;
U.S. Patent Application Publication No. 2015/0102109;
U.S. Patent Application Publication No. 2015/0115035;
U.S. Patent Application Publication No. 2015/0127791;
U.S. Patent Application Publication No. 2015/0128116;
U.S. Patent Application Publication No. 2015/0129659;
U.S. Patent Application Publication No. 2015/0133047;
U.S. Patent Application Publication No. 2015/0134470;
U.S. Patent Application Publication No. 2015/0136851;
U.S. Patent Application Publication No. 2015/0136854;
U.S. Patent Application Publication No. 2015/0142492;
U.S. Patent Application Publication No. 2015/0144692;
U.S. Patent Application Publication No. 2015/0144698;
U.S. Patent Application Publication No. 2015/0144701;
U.S. Patent Application Publication No. 2015/0149946;
U.S. Patent Application Publication No. 2015/0161429;
U.S. Patent Application Publication No. 2015/0169925;
U.S. Patent Application Publication No. 2015/0169929;
U.S. Patent Application Publication No. 2015/0178523;
U.S. Patent Application Publication No. 2015/0178534;
U.S. Patent Application Publication No. 2015/0178535;
U.S. Patent Application Publication No. 2015/0178536;
U.S. Patent Application Publication No. 2015/0178537;
U.S. Patent Application Publication No. 2015/0181093;
U.S. Patent Application Publication No. 2015/0181109;
U.S. patent application Ser. No. 13/367,978 for a Laser Scanning Module Employing an Elastomeric U-Hinge Based Laser Scanning Assembly, filed Feb. 7, 2012 (Feng et al.);
U.S. patent application Ser. No. 29/458,405 for an Electronic Device, filed Jun. 19, 2013 (Fitch et al.);
U.S. patent application Ser. No. 29/459,620 for an Electronic Device Enclosure, filed Jul. 2, 2013 (London et al.);
U.S. patent application Ser. No. 29/468,118 for an Electronic Device Case, filed Sep. 26, 2013 (Oberpriller et al.);
U.S. patent application Ser. No. 14/150,393 for Indicia-reader Having Unitary Construction Scanner, filed Jan. 8, 2014 (Colavito et al.);
U.S. patent application Ser. No. 14/200,405 for Indicia Reader for Size-Limited Applications filed Mar. 7, 2014 (Feng et al.);
U.S. patent application Ser. No. 14/231,898 for Hand-Mounted Indicia-Reading Device with Finger Motion Triggering filed Apr. 1, 2014 (Van Horn et al.);
U.S. patent application Ser. No. 29/486,759 for an Imaging Terminal, filed Apr. 2, 2014 (Oberpriller et al.);
U.S. patent application Ser. No. 14/257,364 for Docking System and Method Using Near Field Communication filed Apr. 21, 2014 (Showering);
U.S. patent application Ser. No. 14/264,173 for Autofocus Lens System for Indicia Readers filed Apr. 29, 2014 (Ackley et al.);
U.S. patent application Ser. No. 14/277,337 for MULTIPURPOSE OPTICAL READER, filed May 14, 2014 (Jovanovski et al.);
U.S. patent application Ser. No. 14/283,282 for TERMINAL HAVING ILLUMINATION AND FOCUS CONTROL filed May 21, 2014 (Liu et al.);
U.S. patent application Ser. No. 14/327,827 for a MOBILE-PHONE ADAPTER FOR ELECTRONIC TRANSACTIONS, filed Jul. 10, 2014 (Hejl);
U.S. patent application Ser. No. 14/334,934 for a SYSTEM AND METHOD FOR INDICIA VERIFICATION, filed Jul. 18, 2014 (Hejl);
U.S. patent application Ser. No. 14/339,708 for LASER SCANNING CODE SYMBOL READING SYSTEM, filed Jul. 24, 2014 (Xian et al.);
U.S. patent application Ser. No. 14/340,627 for an AXIALLY REINFORCED FLEXIBLE SCAN ELEMENT, filed Jul. 25, 2014 (Rueblinger et al.);
U.S. patent application Ser. No. 14/446,391 for MULTIFUNCTION POINT OF SALE APPARATUS WITH OPTICAL SIGNATURE CAPTURE filed Jul. 30, 2014 (Good et al.);
U.S. patent application Ser. No. 14/452,697 for INTERACTIVE INDICIA READER, filed Aug. 6, 2014 (Todeschini);
U.S. patent application Ser. No. 14/453,019 for DIMENSIONING SYSTEM WITH GUIDED ALIGNMENT, filed Aug. 6, 2014 (Li et al.);
U.S. patent application Ser. No. 14/462,801 for MOBILE COMPUTING DEVICE WITH DATA COGNITION SOFTWARE, filed on Aug. 19, 2014 (Todeschini et al.);
U.S. patent application Ser. No. 14/483,056 for VARIABLE DEPTH OF FIELD BARCODE SCANNER filed Sep. 10, 2014 (McCloskey et al.);
U.S. patent application Ser. No. 14/513,808 for IDENTIFYING INVENTORY ITEMS IN A STORAGE FACILITY filed Oct. 14, 2014 (Singel et al.);
U.S. patent application Ser. No. 14/519,195 for HANDHELD DIMENSIONING SYSTEM WITH FEEDBACK filed Oct. 21, 2014 (Laffargue et al.);
U.S. patent application Ser. No. 14/519,179 for DIMENSIONING SYSTEM WITH MULTIPATH INTERFERENCE MITIGATION filed Oct. 21, 2014 (Thuries et al.);
U.S. patent application Ser. No. 14/519,211 for SYSTEM AND METHOD FOR DIMENSIONING filed Oct. 21, 2014 (Ackley et al.);
U.S. patent application Ser. No. 14/519,233 for HANDHELD DIMENSIONER WITH DATA-QUALITY INDICATION filed Oct. 21, 2014 (Laffargue et al.);
U.S. patent application Ser. No. 14/519,249 for HANDHELD DIMENSIONING SYSTEM WITH MEASUREMENT-CONFORMANCE FEEDBACK filed Oct. 21, 2014 (Ackley et al.);
U.S. patent application Ser. No. 14/527,191 for METHOD AND SYSTEM FOR RECOGNIZING SPEECH USING WILDCARDS IN AN EXPECTED RESPONSE filed Oct. 29, 2014 (Braho et al.);
U.S. patent application Ser. No. 14/529,563 for ADAPTABLE INTERFACE FOR A MOBILE COMPUTING DEVICE filed Oct. 31, 2014 (Schoon et al.);
U.S. patent application Ser. No. 14/529,857 for BARCODE READER WITH SECURITY FEATURES filed Oct. 31, 2014 (Todeschini et al.);
U.S. patent application Ser. No. 14/398,542 for PORTABLE ELECTRONIC DEVICES HAVING A SEPARATE LOCATION TRIGGER UNIT FOR USE IN CONTROLLING AN APPLICATION UNIT filed Nov. 3, 2014 (Bian et al.);
U.S. patent application Ser. No. 14/531,154 for DIRECTING AN INSPECTOR THROUGH AN INSPECTION filed Nov. 3, 2014 (Miller et al.);
U.S. patent application Ser. No. 14/533,319 for BARCODE SCANNING SYSTEM USING WEARABLE DEVICE WITH EMBEDDED CAMERA filed Nov. 5, 2014 (Todeschini);
U.S. patent application Ser. No. 14/535,764 for CONCATENATED EXPECTED RESPONSES FOR SPEECH RECOGNITION filed Nov. 7, 2014 (Braho et al.);
U.S. patent application Ser. No. 14/568,305 for AUTO-CONTRAST VIEWFINDER FOR AN INDICIA READER filed Dec. 12, 2014 (Todeschini);
U.S. patent application Ser. No. 14/573,022 for DYNAMIC DIAGNOSTIC INDICATOR GENERATION filed Dec. 17, 2014 (Goldsmith);
U.S. patent application Ser. No. 14/578,627 for SAFETY SYSTEM AND METHOD filed Dec. 22, 2014 (Ackley et al.);
U.S. patent application Ser. No. 14/580,262 for MEDIA GATE FOR THERMAL TRANSFER PRINTERS filed Dec. 23, 2014 (Bowles);
U.S. patent application Ser. No. 14/590,024 for SHELVING AND PACKAGE LOCATING SYSTEMS FOR DELIVERY VEHICLES filed Jan. 6, 2015 (Payne);
U.S. patent application Ser. No. 14/596,757 for SYSTEM AND METHOD FOR DETECTING BARCODE PRINTING ERRORS filed Jan. 14, 2015 (Ackley);
U.S. patent application Ser. No. 14/416,147 for OPTICAL READING APPARATUS HAVING VARIABLE SETTINGS filed Jan. 21, 2015 (Chen et al.);
U.S. patent application Ser. No. 14/614,706 for DEVICE FOR SUPPORTING AN ELECTRONIC TOOL ON A USER'S HAND filed Feb. 5, 2015 (Oberpriller et al.);
U.S. patent application Ser. No. 14/614,796 for CARGO APPORTIONMENT TECHNIQUES filed Feb. 5, 2015 (Morton et al.);
U.S. patent application Ser. No. 29/516,892 for TABLE COMPUTER filed Feb. 6, 2015 (Bidwell et al.);
U.S. patent application Ser. No. 14/619,093 for METHODS FOR TRAINING A SPEECH RECOGNITION SYSTEM filed Feb. 11, 2015 (Pecorari);
U.S. patent application Ser. No. 14/628,708 for DEVICE, SYSTEM, AND METHOD FOR DETERMINING THE STATUS OF CHECKOUT LANES filed Feb. 23, 2015 (Todeschini);
U.S. patent application Ser. No. 14/630,841 for TERMINAL INCLUDING IMAGING ASSEMBLY filed Feb. 25, 2015 (Gomez et al.);
U.S. patent application Ser. No. 14/635,346 for SYSTEM AND METHOD FOR RELIABLE STORE-AND-FORWARD DATA HANDLING BY ENCODED INFORMATION READING TERMINALS filed Mar. 2, 2015 (Sevier);
U.S. patent application Ser. No. 29/519,017 for SCANNER filed Mar. 2, 2015 (Zhou et al.);
U.S. patent application Ser. No. 14/405,278 for DESIGN PATTERN FOR SECURE STORE filed Mar. 9, 2015 (Zhu et al.);
U.S. patent application Ser. No. 14/660,970 for DECODABLE INDICIA READING TERMINAL WITH COMBINED ILLUMINATION filed Mar. 18, 2015 (Kearney et al.);
U.S. patent application Ser. No. 14/661,013 for REPROGRAMMING SYSTEM AND METHOD FOR DEVICES INCLUDING PROGRAMMING SYMBOL filed Mar. 18, 2015 (Soule et al.);
U.S. patent application Ser. No. 14/662,922 for MULTIFUNCTION POINT OF SALE SYSTEM filed Mar. 19, 2015 (Van Horn et al.);
U.S. patent application Ser. No. 14/663,638 for VEHICLE MOUNT COMPUTER WITH CONFIGURABLE IGNITION SWITCH BEHAVIOR filed Mar. 20, 2015 (Davis et al.);
U.S. patent application Ser. No. 14/664,063 for METHOD AND APPLICATION FOR SCANNING A BARCODE WITH A SMART DEVICE WHILE CONTINUOUSLY RUNNING AND DISPLAYING AN APPLICATION ON THE SMART DEVICE DISPLAY filed Mar. 20, 2015 (Todeschini);
U.S. patent application Ser. No. 14/669,280 for TRANSFORMING COMPONENTS OF A WEB PAGE TO VOICE PROMPTS filed Mar. 26, 2015 (Funyak et al.);
U.S. patent application Ser. No. 14/674,329 for AIMER FOR BARCODE SCANNING filed Mar. 31, 2015 (Bidwell);
U.S. patent application Ser. No. 14/676,109 for INDICIA READER filed Apr. 1, 2015 (Huck);
U.S. patent application Ser. No. 14/676,327 for DEVICE MANAGEMENT PROXY FOR SECURE DEVICES filed Apr. 1, 2015 (Yeakley et al.);
U.S. patent application Ser. No. 14/676,898 for NAVIGATION SYSTEM CONFIGURED TO INTEGRATE MOTION SENSING DEVICE INPUTS filed Apr. 2, 2015 (Showering);
U.S. patent application Ser. No. 14/679,275 for DIMENSIONING SYSTEM CALIBRATION SYSTEMS AND METHODS filed Apr. 6, 2015 (Laffargue et al.);
U.S. patent application Ser. No. 29/523,098 for HANDLE FOR A TABLET COMPUTER filed Apr. 7, 2015 (Bidwell et al.);
U.S. patent application Ser. No. 14/682,615 for SYSTEM AND METHOD FOR POWER MANAGEMENT OF MOBILE DEVICES filed Apr. 9, 2015 (Murawski et al.);
U.S. patent application Ser. No. 14/686,822 for MULTIPLE PLATFORM SUPPORT SYSTEM AND METHOD filed Apr. 15, 2015 (Qu et al.);
U.S. patent application Ser. No. 14/687,289 for SYSTEM FOR COMMUNICATION VIA A PERIPHERAL HUB filed Apr. 15, 2015 (Kohtz et al.);
U.S. patent application Ser. No. 29/524,186 for SCANNER filed Apr. 17, 2015 (Zhou et al.);
U.S. patent application Ser. No. 14/695,364 for MEDICATION MANAGEMENT SYSTEM filed Apr. 24, 2015 (Sewell et al.);
U.S. patent application Ser. No. 14/695,923 for SECURE UNATTENDED NETWORK AUTHENTICATION filed Apr. 24, 2015 (Kubler et al.);
U.S. patent application Ser. No. 29/525,068 for TABLET COMPUTER WITH REMOVABLE SCANNING DEVICE filed Apr. 27, 2015 (Schulte et al.);
U.S. patent application Ser. No. 14/699,436 for SYMBOL READING SYSTEM HAVING PREDICTIVE DIAGNOSTICS filed Apr. 29, 2015 (Nahill et al.);
U.S. patent application Ser. No. 14/702,110 for SYSTEM AND METHOD FOR REGULATING BARCODE DATA INJECTION INTO A RUNNING APPLICATION ON A SMART DEVICE filed May 1, 2015 (Todeschini et al.);
U.S. patent application Ser. No. 14/702,979 for TRACKING BATTERY CONDITIONS filed May 4, 2015 (Young et al.);
U.S. patent application Ser. No. 14/704,050 for INTERMEDIATE LINEAR POSITIONING filed May 5, 2015 (Charpentier et al.);
U.S. patent application Ser. No. 14/705,012 for HANDS-FREE HUMAN MACHINE INTERFACE RESPONSIVE TO A DRIVER OF A VEHICLE filed May 6, 2015 (Fitch et al.);
U.S. patent application Ser. No. 14/705,407 for METHOD AND SYSTEM TO PROTECT SOFTWARE-BASED NETWORK-CONNECTED DEVICES FROM ADVANCED PERSISTENT THREAT filed May 6, 2015 (Hussey et al.);
U.S. patent application Ser. No. 14/707,037 for SYSTEM AND METHOD FOR DISPLAY OF INFORMATION USING A VEHICLE-MOUNT COMPUTER filed May 8, 2015 (Chamberlin);
U.S. patent application Ser. No. 14/707,123 for APPLICATION INDEPENDENT DEX/UCS INTERFACE filed May 8, 2015 (Pape);
U.S. patent application Ser. No. 14/707,492 for METHOD AND APPARATUS FOR READING OPTICAL INDICIA USING A PLURALITY OF DATA SOURCES filed May 8, 2015 (Smith et al.);
U.S. patent application Ser. No. 14/710,666 for PRE-PAID USAGE SYSTEM FOR ENCODED INFORMATION READING TERMINALS filed May 13, 2015 (Smith);
U.S. patent application Ser. No. 29/526,918 for CHARGING BASE filed May 14, 2015 (Fitch et al.);
U.S. patent application Ser. No. 14/715,672 for AUGMENTED REALITY ENABLED HAZARD DISPLAY filed May 19, 2015 (Venkatesha et al.);
U.S. patent application Ser. No. 14/715,916 for EVALUATING IMAGE VALUES filed May 19, 2015 (Ackley);
U.S. patent application Ser. No. 14/722,608 for INTERACTIVE USER INTERFACE FOR CAPTURING A DOCUMENT IN AN IMAGE SIGNAL filed May 27, 2015 (Showering et al.);
U.S. patent application Ser. No. 29/528,165 for IN-COUNTER BARCODE SCANNER filed May 27, 2015 (Oberpriller et al.);
U.S. patent application Ser. No. 14/724,134 for ELECTRONIC DEVICE WITH WIRELESS PATH SELECTION CAPABILITY filed May 28, 2015 (Wang et al.);
U.S. patent application Ser. No. 14/724,849 for METHOD OF PROGRAMMING THE DEFAULT CABLE INTERFACE SOFTWARE IN AN INDICIA READING DEVICE filed May 29, 2015 (Barten);
U.S. patent application Ser. No. 14/724,908 for IMAGING APPARATUS HAVING IMAGING ASSEMBLY filed May 29, 2015 (Barber et al.);
U.S. patent application Ser. No. 14/725,352 for APPARATUS AND METHODS FOR MONITORING ONE OR MORE PORTABLE DATA TERMINALS (Caballero et al.);
U.S. patent application Ser. No. 29/528,590 for ELECTRONIC DEVICE filed May 29, 2015 (Fitch et al.);
U.S. patent application Ser. No. 29/528,890 for MOBILE COMPUTER HOUSING filed Jun. 2, 2015 (Fitch et al.);
U.S. patent application Ser. No. 14/728,397 for DEVICE MANAGEMENT USING VIRTUAL INTERFACES CROSS-REFERENCE TO RELATED APPLICATIONS filed Jun. 2, 2015 (Caballero);
U.S. patent application Ser. No. 14/732,870 for DATA COLLECTION MODULE AND SYSTEM filed Jun. 8, 2015 (Powilleit);
U.S. patent application Ser. No. 29/529,441 for INDICIA READING DEVICE filed Jun. 8, 2015 (Zhou et al.);
U.S. patent application Ser. No. 14/735,717 for INDICIA-READING SYSTEMS HAVING AN INTERFACE WITH A USER'S NERVOUS SYSTEM filed Jun. 10, 2015 (Todeschini);
U.S. patent application Ser. No. 14/738,038 for METHOD OF AND SYSTEM FOR DETECTING OBJECT WEIGHING INTERFERENCES filed Jun. 12, 2015 (Amundsen et al.);
U.S. patent application Ser. No. 14/740,320 for TACTILE SWITCH FOR A MOBILE ELECTRONIC DEVICE filed Jun. 16, 2015 (Bandringa);
U.S. patent application Ser. No. 14/740,373 for CALIBRATING A VOLUME DIMENSIONER filed Jun. 16, 2015 (Ackley et al.);
U.S. patent application Ser. No. 14/742,818 for INDICIA READING SYSTEM EMPLOYING DIGITAL GAIN CONTROL filed Jun. 18, 2015 (Xian et al.);
U.S. patent application Ser. No. 14/743,257 for WIRELESS MESH POINT PORTABLE DATA TERMINAL filed Jun. 18, 2015 (Wang et al.);
U.S. patent application Ser. No. 29/530,600 for CYCLONE filed Jun. 18, 2015 (Vargo et al);
U.S. patent application Ser. No. 14/744,633 for IMAGING APPARATUS COMPRISING IMAGE SENSOR ARRAY HAVING SHARED GLOBAL SHUTTER CIRCUITRY filed Jun. 19, 2015 (Wang);
U.S. patent application Ser. No. 14/744,836 for CLOUD-BASED SYSTEM FOR READING OF DECODABLE INDICIA filed Jun. 19, 2015 (Todeschini et al.);
U.S. patent application Ser. No. 14/745,006 for SELECTIVE OUTPUT OF DECODED MESSAGE DATA filed Jun. 19, 2015 (Todeschini et al.);
U.S. patent application Ser. No. 14/747,197 for OPTICAL PATTERN PROJECTOR filed Jun. 23, 2015 (Thuries et al.);
U.S. patent application Ser. No. 14/747,490 for DUAL-PROJECTOR THREE-DIMENSIONAL SCANNER filed Jun. 23, 2015 (Jovanovski et al.); and
U.S. patent application Ser. No. 14/748,446 for CORDLESS INDICIA READER WITH A MULTIFUNCTION COIL FOR WIRELESS CHARGING AND EAS DEACTIVATION, filed Jun. 24, 2015 (Xie et al.).

In the specification and/or figures, typical embodiments of the invention have been disclosed. The present invention is not limited to such exemplary embodiments. The use of the term “and/or” includes any and all combinations of one or more of the associated listed items. The figures are schematic representations and so are not necessarily drawn to scale. Unless otherwise noted, specific terms have been used in a generic and descriptive sense and not for purposes of limitation.

Claims

1. A method, comprising: initializing a dimensioning system by: at a range camera, capturing one or more initial reference images of a measurement platform and surrounding area;at a processor: generating a reference depth map from each initial reference image;generating and storing to a memory a background model from the reference depth maps;testing the dimensioning system for a scene change by: at the range camera, capturing a subsequent image of the measurement platform and surrounding area;at the processor: generating a current depth map from the subsequent image;comparing each pixel of the current depth map with a corresponding pixel of the background model; andcounting a number of pixels Pv of the current depth map that differ absolutely from the background model by more than the prescribed threshold THRESH1, and if the number of pixels Pv is greater than a threshold THRESH2, determining that a significant change in the image has occurred.
2. The method according to claim 1, where the testing is carried out on a periodic basis.
3. The method according to claim 1, further comprising executing a dimensioning process to measure the dimensions of an object on the measurement platform.
4. The method according to claim 3, where the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform.
5. The method according to claim 3, where the testing is carried out prior to each measurement of dimensions of an object on the measurement platform.
6. The method according to claim 1, further comprising generating an alert upon determining that a significant scene change has occurred.
7. The method according to claim 1, further comprising upon determining that a significant scene change has occurred, repeating the initializing.
8. A dimensioning system, comprising: a measurement platform;a range camera mounted so as to capture an image of the measurement platform and surrounding area;a processor programmed to carry out the following actions:initialize the dimensioning system by: receiving one or more initial reference images of the measurement platform and surrounding area from the range camera;generating and storing to a memory a background model from the one or more captured initial reference images;test the dimensioning system for a scene change by: receiving a subsequent image of the platform area from the range camera;generating a current depth map from the subsequent image;comparing each pixel of the current depth map with a corresponding pixel of the background model; andcounting a number of pixels Pv of the current depth map that differ absolutely from the background model by more than the prescribed threshold THRESH1, and if the number of pixels Pv is greater than a threshold THRESH2, determining that a significant change in the image has occurred.
9. The system according to claim 8, where the testing is carried out on a periodic basis.
10. The system according to claim 8, further comprising the processor executing a dimensioning process to measure dimensions of an object on the measurement platform.
11. The system according to claim 10, where the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform.
12. The system according to claim 10, where the testing is carried out prior to each measurement of dimensions of an object on the measurement platform.
13. The system according to claim 8, further comprising the processor generating an alert upon determining that a significant scene change has occurred.
14. The system according to claim 8, further comprising upon determining that a significant scene change has occurred, the processor repeating the initializing.
15. A method, comprising: initializing a dimensioning system by: at a range camera, capturing an initial reference image of a platform and surrounding area;at a processor, generating a three-dimensional container around the platform and storing the container to memory; andat the processor, determining a count of support points in the container from the initial reference image;testing the dimensioning system for a scene change by: at the range camera, capturing a subsequent image of the measurement platform and surrounding area;at the processor: counting support points in the subsequent image that are in the container;comparing the count of support points in the container in the subsequent image with the count of support points in the container in the initial reference image;based on the comparison, determining if a prescribed difference in the counts is present; andupon determining that a prescribed difference in the counts exists establishing that a significant scene change has occurred.
16. The method according to claim 15, where the testing is carried out on a periodic basis.
17. The method according to claim 15, further comprising executing a dimensioning process to measure dimensions of an object on the platform.
18. The method according to claim 17, where the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform.
19. The method according to claim 17, where the testing is carried out prior to each measurement of dimensions of an object on the measurement platform.
20. The method according to claim 17, further comprising generating an alert upon determining that a significant scene change has occurred.
21. The method according to claim 17, where the container comprises a right prism with a base approximating a convex polygon, where the base is parallel to a congruent convex polygon that bounds the measurement platform, and where the prism's height equals twice a maximum support distance.
22. The method according to claim 15, where the container comprises a right cylinder with a circular base, where the base is parallel to a congruent circle that bounds the measurement platform, and where the cylinder's height equals twice the maximum support distance.
23. The method according to claim 15, comprising: when a significant scene change is deemed to have occurred, searching the scene for the measurement platform at a location coplanar therewith.
24. The method according to claim 15, further comprising upon establishing that a significant scene change has occurred, repeating the initializing.
25. A dimensioning system, comprising: a measurement platform;a range camera mounted so as to capture an image of the measurement platform and surrounding area;a processor programmed to carry out the following actions: initialize the dimensioning system by: receiving an initial reference image of a platform area from the range camera;generating a three-dimensional container around the measurement platform and storing the container to memory; anddetermining a count of support points in the container from the initial reference image;test the dimensioning system for a scene change by: receiving a subsequent image of the measurement platform and surrounding area from the range camera;counting support points in the subsequent image that are in the container;comparing the count of support points in the container in the subsequent image with the count of support points in the container in the initial reference image;based on the comparison, determining if a prescribed difference in the counts of support points is present; andupon determining that a prescribed difference in the counts exists establishing that a significant scene change has occurred.
26. The system according to claim 25, where the testing is carried out on a periodic basis.
27. The system according to claim 25, further comprising the processor executing a dimensioning process to measure dimensions of an object on the measurement platform.
28. The system according to claim 27, where the testing is carried out whenever a prescribed period of inactivity in measuring dimensions of an object on the measurement platform.
29. The system according to claim 27, where the testing is carried out prior to each measurement of dimensions of an object on the measurement platform.
30. The system according to claim 25, further comprising the processor generating an alert upon determining that a significant scene change has occurred.
31. The system according to claim 25, where the container comprises a right prism with a base approximating a convex polygon, where the base is parallel to a congruent convex polygon that bounds the measurement platform, and where the prism's height equals twice the maximum support distance.
32. The system according to claim 25, where the container comprises a right cylinder with a circular base, where the base is parallel to a congruent circle that bounds the measurement platform, and where the cylinder's height equals twice the maximum support distance.
33. The system according to claim 25, further comprising when a significant scene change is deemed to have occurred, the processor searching the scene for the measurement platform at a location coplanar therewith.
34. The system according to claim 25, further comprising the processor repeating the initializing upon establishing that a significant scene change has occurred.

US Referenced Citations (876)

Number	Name	Date	Kind
3971065	Bayer	Jul 1976	A
4026031	Siddall et al.	May 1977	A
4279328	Ahlbom	Jul 1981	A
4398811	Nishioka et al.	Aug 1983	A
4495559	Gelatt, Jr.	Jan 1985	A
4730190	Win et al.	Mar 1988	A
4803639	Steele et al.	Feb 1989	A
5184733	Amarson et al.	Feb 1993	A
5198648	Hibbard	Mar 1993	A
5220536	Stringer et al.	Jun 1993	A
5331118	Jensen	Jul 1994	A
5359185	Hanson	Oct 1994	A
5384901	Glassner et al.	Jan 1995	A
5548707	LoNegro et al.	Aug 1996	A
5555090	Schmutz	Sep 1996	A
5561526	Huber et al.	Oct 1996	A
5590060	Granville et al.	Dec 1996	A
5606534	Stringer et al.	Feb 1997	A
5619245	Kessler et al.	Apr 1997	A
5655095	LoNegro et al.	Aug 1997	A
5661561	Wurz et al.	Aug 1997	A
5699161	Woodworth	Dec 1997	A
5729750	Ishida	Mar 1998	A
5730252	Herbinet	Mar 1998	A
5732147	Tao	Mar 1998	A
5734476	Dlugos	Mar 1998	A
5737074	Haga et al.	Apr 1998	A
5748199	Palm	May 1998	A
5767962	Suzuki et al.	Jun 1998	A
5831737	Stringer et al.	Nov 1998	A
5850370	Stringer et al.	Dec 1998	A
5850490	Johnson	Dec 1998	A
5869827	Rando	Feb 1999	A
5870220	Migdal et al.	Feb 1999	A
5900611	Hecht	May 1999	A
5923428	Woodworth	Jul 1999	A
5929856	LoNegro et al.	Jul 1999	A
5938710	Lanza et al.	Aug 1999	A
5959568	Woolley	Sep 1999	A
5960098	Tao	Sep 1999	A
5969823	Wurz et al.	Oct 1999	A
5978512	Kim et al.	Nov 1999	A
5979760	Freyman et al.	Nov 1999	A
5988862	Kacyra et al.	Nov 1999	A
5991041	Woodworth	Nov 1999	A
6009189	Schaack	Dec 1999	A
6025847	Marks	Feb 2000	A
6035067	Ponticos	Mar 2000	A
6049386	Stringer et al.	Apr 2000	A
6053409	Brobst et al.	Apr 2000	A
6064759	Buckley et al.	May 2000	A
6067110	Nonaka et al.	May 2000	A
6069696	McQueen et al.	May 2000	A
6115114	Berg et al.	Sep 2000	A
6137577	Woodworth	Oct 2000	A
6177999	Wurz et al.	Jan 2001	B1
6189223	Haug	Feb 2001	B1
6232597	Kley	May 2001	B1
6236403	Chaki	May 2001	B1
6246468	Dimsdale	Jun 2001	B1
6333749	Reinhardt et al.	Dec 2001	B1
6336587	He et al.	Jan 2002	B1
6369401	Lee	Apr 2002	B1
6373579	Ober et al.	Apr 2002	B1
6429803	Kumar	Aug 2002	B1
6457642	Good et al.	Oct 2002	B1
6507406	Yagi et al.	Jan 2003	B1
6517004	Good et al.	Feb 2003	B2
6519550	D'Hooge et al.	Feb 2003	B1
6535776	Tobin et al.	Mar 2003	B1
6674904	McQueen	Jan 2004	B1
6705526	Zhu et al.	Mar 2004	B1
6781621	Gobush et al.	Aug 2004	B1
6824058	Patel et al.	Nov 2004	B2
6832725	Gardiner et al.	Dec 2004	B2
6858857	Pease et al.	Feb 2005	B2
6922632	Foxlin	Jul 2005	B2
6971580	Zhu et al.	Dec 2005	B2
6995762	Pavlidis et al.	Feb 2006	B1
7057632	Yamawaki et al.	Jun 2006	B2
7085409	Sawhney et al.	Aug 2006	B2
7086162	Tyroler	Aug 2006	B2
7104453	Zhu et al.	Sep 2006	B1
7128266	Zhu et al.	Oct 2006	B2
7137556	Bonner et al.	Nov 2006	B1
7159783	Walczyk et al.	Jan 2007	B2
7161688	Bonner et al.	Jan 2007	B1
7205529	Andersen et al.	Apr 2007	B2
7214954	Schopp	May 2007	B2
7277187	Smith et al.	Oct 2007	B2
7307653	Dutta	Dec 2007	B2
7310431	Gokturk et al.	Dec 2007	B2
7353137	Vock et al.	Apr 2008	B2
7413127	Ehrhart et al.	Aug 2008	B2
7509529	Colucci et al.	Mar 2009	B2
7527205	Zhu	May 2009	B2
7586049	Wurz	Sep 2009	B2
7602404	Reinhardt et al.	Oct 2009	B1
7639722	Paxton et al.	Dec 2009	B1
7726575	Wang et al.	Jun 2010	B2
7780084	Zhang et al.	Aug 2010	B2
7788883	Buckley et al.	Sep 2010	B2
7974025	Topliss	Jul 2011	B2
8027096	Feng et al.	Sep 2011	B2
8028501	Buckley et al.	Oct 2011	B2
8050461	Shpunt et al.	Nov 2011	B2
8055061	Katano	Nov 2011	B2
8072581	Breiholz	Dec 2011	B1
8102395	Kondo et al.	Jan 2012	B2
8132728	Dwinell et al.	Mar 2012	B2
8134717	Pangrazio et al.	Mar 2012	B2
8149224	Kuo et al.	Apr 2012	B1
8194097	Xiao et al.	Jun 2012	B2
8201737	Palacios Durazo et al.	Jun 2012	B1
8212158	Wiest	Jul 2012	B2
8212889	Chanas et al.	Jul 2012	B2
8228510	Pangrazio et al.	Jul 2012	B2
8230367	Bell et al.	Jul 2012	B2
8294969	Plesko	Oct 2012	B2
8305458	Hara	Nov 2012	B2
8310656	Zalewski	Nov 2012	B2
8313380	Zalewski et al.	Nov 2012	B2
8317105	Kotlarsky et al.	Nov 2012	B2
8322622	Liu	Dec 2012	B2
8339462	Stec et al.	Dec 2012	B2
8350959	Topliss et al.	Jan 2013	B2
8351670	Ijiri et al.	Jan 2013	B2
8366005	Kotlarsky et al.	Feb 2013	B2
8371507	Haggerty et al.	Feb 2013	B2
8376233	Van Horn et al.	Feb 2013	B2
8381976	Mohideen et al.	Feb 2013	B2
8381979	Franz	Feb 2013	B2
8390909	Plesko	Mar 2013	B2
8408464	Zhu et al.	Apr 2013	B2
8408468	Horn et al.	Apr 2013	B2
8408469	Good	Apr 2013	B2
8424768	Rueblinger et al.	Apr 2013	B2
8437539	Komatsu et al.	May 2013	B2
8441749	Brown et al.	May 2013	B2
8448863	Xian et al.	May 2013	B2
8457013	Essinger et al.	Jun 2013	B2
8459557	Havens et al.	Jun 2013	B2
8463079	Ackley et al.	Jun 2013	B2
8469272	Kearney	Jun 2013	B2
8474712	Kearney et al.	Jul 2013	B2
8479992	Kotlarsky et al.	Jul 2013	B2
8490877	Kearney	Jul 2013	B2
8517271	Kotlarsky et al.	Aug 2013	B2
8523076	Good	Sep 2013	B2
8528818	Ehrhart et al.	Sep 2013	B2
8544737	Gomez et al.	Oct 2013	B2
8548420	Grunow et al.	Oct 2013	B2
8550335	Samek et al.	Oct 2013	B2
8550354	Gannon et al.	Oct 2013	B2
8550357	Kearney	Oct 2013	B2
8556174	Kosecki et al.	Oct 2013	B2
8556176	Van Horn et al.	Oct 2013	B2
8556177	Hussey et al.	Oct 2013	B2
8559767	Barber et al.	Oct 2013	B2
8561895	Gomez et al.	Oct 2013	B2
8561903	Sauerwein	Oct 2013	B2
8561905	Edmonds et al.	Oct 2013	B2
8565107	Pease et al.	Oct 2013	B2
8570343	Halstead	Oct 2013	B2
8571307	Li et al.	Oct 2013	B2
8576390	Nunnink	Nov 2013	B1
8579200	Samek et al.	Nov 2013	B2
8583924	Caballero et al.	Nov 2013	B2
8584945	Wang et al.	Nov 2013	B2
8587595	Wang	Nov 2013	B2
8587697	Hussey et al.	Nov 2013	B2
8588869	Sauerwein et al.	Nov 2013	B2
8590789	Nahill et al.	Nov 2013	B2
8594425	Gurman et al.	Nov 2013	B2
8596539	Havens et al.	Dec 2013	B2
8596542	Havens et al.	Dec 2013	B2
8596543	Havens et al.	Dec 2013	B2
8599271	Havens et al.	Dec 2013	B2
8599957	Peake et al.	Dec 2013	B2
8600158	Li et al.	Dec 2013	B2
8600167	Showering	Dec 2013	B2
8602309	Longacre et al.	Dec 2013	B2
8608053	Meier et al.	Dec 2013	B2
8608071	Liu et al.	Dec 2013	B2
8611309	Wang et al.	Dec 2013	B2
8615487	Gomez et al.	Dec 2013	B2
8621123	Caballero	Dec 2013	B2
8622303	Meier et al.	Jan 2014	B2
8628013	Ding	Jan 2014	B2
8628015	Wang et al.	Jan 2014	B2
8628016	Winegar	Jan 2014	B2
8629926	Wang	Jan 2014	B2
8630491	Longacre et al.	Jan 2014	B2
8635309	Berthiaume et al.	Jan 2014	B2
8636200	Kearney	Jan 2014	B2
8636212	Nahill et al.	Jan 2014	B2
8636215	Ding et al.	Jan 2014	B2
8636224	Wang	Jan 2014	B2
8638806	Wang et al.	Jan 2014	B2
8640958	Lu et al.	Feb 2014	B2
8640960	Wang et al.	Feb 2014	B2
8643717	Li et al.	Feb 2014	B2
8646692	Meier et al.	Feb 2014	B2
8646694	Wang et al.	Feb 2014	B2
8657200	Ren et al.	Feb 2014	B2
8659397	Vargo et al.	Feb 2014	B2
8668149	Good	Mar 2014	B2
8678285	Kearney	Mar 2014	B2
8678286	Smith et al.	Mar 2014	B2
8682077	Longacre	Mar 2014	B1
D702237	Oberpriller et al.	Apr 2014	S
8687282	Feng et al.	Apr 2014	B2
8692927	Pease et al.	Apr 2014	B2
8695880	Bremer et al.	Apr 2014	B2
8698949	Grunow et al.	Apr 2014	B2
8702000	Barber et al.	Apr 2014	B2
8717494	Gannon	May 2014	B2
8720783	Biss et al.	May 2014	B2
8723804	Fletcher et al.	May 2014	B2
8723904	Marty et al.	May 2014	B2
8727223	Wang	May 2014	B2
8740082	Wilz	Jun 2014	B2
8740085	Furlong et al.	Jun 2014	B2
8746563	Hennick et al.	Jun 2014	B2
8750445	Peake et al.	Jun 2014	B2
8752766	Xian et al.	Jun 2014	B2
8756059	Braho et al.	Jun 2014	B2
8757495	Qu et al.	Jun 2014	B2
8760563	Koziol et al.	Jun 2014	B2
8763909	Reed et al.	Jul 2014	B2
8777108	Coyle	Jul 2014	B2
8777109	Oberpriller et al.	Jul 2014	B2
8779898	Havens et al.	Jul 2014	B2
8781520	Payne et al.	Jul 2014	B2
8783573	Havens et al.	Jul 2014	B2
8789757	Barten	Jul 2014	B2
8789758	Hawley et al.	Jul 2014	B2
8789759	Xian et al.	Jul 2014	B2
8792688	Unsworth	Jul 2014	B2
8794520	Wang et al.	Aug 2014	B2
8794522	Ehrhart	Aug 2014	B2
8794525	Amundsen et al.	Aug 2014	B2
8794526	Wang et al.	Aug 2014	B2
8798367	Ellis	Aug 2014	B2
8807431	Wang et al.	Aug 2014	B2
8807432	Van Horn et al.	Aug 2014	B2
8810779	Hilde	Aug 2014	B1
8820630	Qu et al.	Sep 2014	B2
8822848	Meagher	Sep 2014	B2
8824692	Sheerin et al.	Sep 2014	B2
8824696	Braho	Sep 2014	B2
8842849	Wahl et al.	Sep 2014	B2
8844822	Kotlarsky et al.	Sep 2014	B2
8844823	Fritz et al.	Sep 2014	B2
8849019	Li et al.	Sep 2014	B2
D716285	Chaney et al.	Oct 2014	S
8851383	Yeakley et al.	Oct 2014	B2
8854633	Laffargue	Oct 2014	B2
8866963	Grunow et al.	Oct 2014	B2
8868421	Braho et al.	Oct 2014	B2
8868519	Maloy et al.	Oct 2014	B2
8868802	Barten	Oct 2014	B2
8868803	Caballero	Oct 2014	B2
8870074	Gannon	Oct 2014	B1
8879639	Sauerwein	Nov 2014	B2
8880426	Smith	Nov 2014	B2
8881983	Havens et al.	Nov 2014	B2
8881987	Wang	Nov 2014	B2
8897596	Passmore et al.	Nov 2014	B1
8903172	Smith	Dec 2014	B2
8908995	Benos et al.	Dec 2014	B2
8910870	Li et al.	Dec 2014	B2
8910875	Ren et al.	Dec 2014	B2
8914290	Hendrickson et al.	Dec 2014	B2
8914788	Pettinelli et al.	Dec 2014	B2
8915439	Feng et al.	Dec 2014	B2
8915444	Havens et al.	Dec 2014	B2
8916789	Woodburn	Dec 2014	B2
8918250	Hollifield	Dec 2014	B2
8918564	Caballero	Dec 2014	B2
8925818	Kosecki et al.	Jan 2015	B2
8928896	Kennington et al.	Jan 2015	B2
8939374	Jovanovski et al.	Jan 2015	B2
8942480	Ellis	Jan 2015	B2
8944313	Williams et al.	Feb 2015	B2
8944327	Meier et al.	Feb 2015	B2
8944332	Harding et al.	Feb 2015	B2
8950678	Germaine et al.	Feb 2015	B2
D723560	Zhou et al.	Mar 2015	S
8967468	Gomez et al.	Mar 2015	B2
8971346	Sevier	Mar 2015	B2
8976030	Cunningham et al.	Mar 2015	B2
8976368	Akel et al.	Mar 2015	B2
8978981	Guan	Mar 2015	B2
8978983	Bremer et al.	Mar 2015	B2
8978984	Hennick et al.	Mar 2015	B2
8985456	Zhu et al.	Mar 2015	B2
8985457	Soule et al.	Mar 2015	B2
8985459	Kearney et al.	Mar 2015	B2
8985461	Gelay et al.	Mar 2015	B2
8988578	Showering	Mar 2015	B2
8988590	Gillet et al.	Mar 2015	B2
8991704	Hopper et al.	Mar 2015	B2
8996194	Davis et al.	Mar 2015	B2
8996384	Funyak et al.	Mar 2015	B2
8998091	Edmonds et al.	Apr 2015	B2
9002641	Showering	Apr 2015	B2
9007368	Laffargue et al.	Apr 2015	B2
9010641	Qu et al.	Apr 2015	B2
9014441	Truyen et al.	Apr 2015	B2
9015513	Murawski et al.	Apr 2015	B2
9016576	Brady et al.	Apr 2015	B2
D730357	Fitch et al.	May 2015	S
9022288	Nahill et al.	May 2015	B2
9030964	Essinger et al.	May 2015	B2
9033240	Smith et al.	May 2015	B2
9033242	Gillet et al.	May 2015	B2
9036054	Koziol et al.	May 2015	B2
9037344	Chamberlin	May 2015	B2
9038911	Xian et al.	May 2015	B2
9038915	Smith	May 2015	B2
D730901	Oberpriller et al.	Jun 2015	S
D730902	Fitch et al.	Jun 2015	S
D733112	Chaney et al.	Jun 2015	S
9047098	Barten	Jun 2015	B2
9047359	Caballero et al.	Jun 2015	B2
9047420	Caballero	Jun 2015	B2
9047525	Barber	Jun 2015	B2
9047531	Showering et al.	Jun 2015	B2
9049640	Wang et al.	Jun 2015	B2
9053055	Caballero	Jun 2015	B2
9053378	Hou et al.	Jun 2015	B1
9053380	Xian et al.	Jun 2015	B2
9057641	Amundsen et al.	Jun 2015	B2
9058526	Powilleit	Jun 2015	B2
9064165	Havens et al.	Jun 2015	B2
9064167	Xian et al.	Jun 2015	B2
9064168	Todeschini et al.	Jun 2015	B2
9064254	Todeschini et al.	Jun 2015	B2
9066032	Wang	Jun 2015	B2
9070032	Corcoran	Jun 2015	B2
D734339	Zhou et al.	Jul 2015	S
D734751	Oberpriller et al.	Jul 2015	S
9082023	Feng et al.	Jul 2015	B2
9082195	Holeva et al.	Jul 2015	B2
9142035	Rotman	Sep 2015	B1
9171278	Kong et al.	Oct 2015	B1
9224022	Ackley et al.	Dec 2015	B2
9224027	Van Horn et al.	Dec 2015	B2
D747321	London et al.	Jan 2016	S
9230140	Ackley	Jan 2016	B1
9233470	Bradski et al.	Jan 2016	B1
9235899	Kirmani et al.	Jan 2016	B1
9443123	Hejl	Jan 2016	B2
9250712	Todeschini	Feb 2016	B1
9258033	Showering	Feb 2016	B2
9262633	Todeschini et al.	Feb 2016	B1
9299013	Curlander et al.	Mar 2016	B1
9310609	Rueblinger et al.	Apr 2016	B2
D757009	Oberpriller et al.	May 2016	S
9342724	McCloskey et al.	May 2016	B2
9375945	Bowles	Jun 2016	B1
D760719	Zhou et al.	Jul 2016	S
9390596	Todeschini	Jul 2016	B1
D762604	Fitch et al.	Aug 2016	S
D762647	Fitch et al.	Aug 2016	S
9412242	Van Horn et al.	Aug 2016	B2
9424749	Reed et al.	Aug 2016	B1
D766244	Zhou et al.	Sep 2016	S
9443222	Singel et al.	Sep 2016	B2
9478113	Xie et al.	Oct 2016	B2
9486921	Straszheim et al.	Nov 2016	B1
9828223	Svensson et al.	Nov 2017	B2
20010027995	Patel et al.	Oct 2001	A1
20010032879	He et al.	Oct 2001	A1
20020054289	Thibault et al.	May 2002	A1
20020067855	Chiu et al.	Jun 2002	A1
20020109835	Goetz	Aug 2002	A1
20020118874	Chung et al.	Aug 2002	A1
20020158873	Williamson	Oct 2002	A1
20020167677	Okada et al.	Nov 2002	A1
20020179708	Zhu et al.	Dec 2002	A1
20020196534	Lizotte et al.	Dec 2002	A1
20030038179	Tsikos et al.	Feb 2003	A1
20030053513	Vatan et al.	Mar 2003	A1
20030063086	Baumberg	Apr 2003	A1
20030078755	Leutz et al.	Apr 2003	A1
20030091227	Chang et al.	May 2003	A1
20030156756	Gokturk et al.	Aug 2003	A1
20030197138	Pease et al.	Oct 2003	A1
20030225712	Cooper et al.	Dec 2003	A1
20030235331	Kawaike et al.	Dec 2003	A1
20040008259	Gokturk et al.	Jan 2004	A1
20040019274	Galloway et al.	Jan 2004	A1
20040024754	Mane et al.	Feb 2004	A1
20040066329	Zeitfuss et al.	Apr 2004	A1
20040073359	Ichijo et al.	Apr 2004	A1
20040083025	Yamanouchi et al.	Apr 2004	A1
20040089482	Ramsden et al.	May 2004	A1
20040098146	Katae et al.	May 2004	A1
20040105580	Hager et al.	Jun 2004	A1
20040118928	Patel et al.	Jun 2004	A1
20040122779	Stickler et al.	Jun 2004	A1
20040132297	Baba et al.	Jul 2004	A1
20040155975	Hart et al.	Aug 2004	A1
20040165090	Ning	Aug 2004	A1
20040184041	Schopp	Sep 2004	A1
20040211836	Patel et al.	Oct 2004	A1
20040214623	Takahashi et al.	Oct 2004	A1
20040233461	Armstrong et al.	Nov 2004	A1
20040258353	Gluckstad et al.	Dec 2004	A1
20050006477	Patel	Jan 2005	A1
20050117215	Lange	Jun 2005	A1
20050128193	Popescu et al.	Jun 2005	A1
20050128196	Popescu et al.	Jun 2005	A1
20050168488	Montague	Aug 2005	A1
20050211782	Martin	Sep 2005	A1
20050257748	Kriesel et al.	Nov 2005	A1
20050264867	Cho et al.	Dec 2005	A1
20060047704	Gopalakrishnan	Mar 2006	A1
20060078226	Zhou	Apr 2006	A1
20060108266	Bowers et al.	May 2006	A1
20060112023	Horhann	May 2006	A1
20060151604	Zhu et al.	Jul 2006	A1
20060159307	Anderson et al.	Jul 2006	A1
20060159344	Shao et al.	Jul 2006	A1
20060213999	Wang et al.	Sep 2006	A1
20060230640	Chen	Oct 2006	A1
20060232681	Okada	Oct 2006	A1
20060255150	Longacre	Nov 2006	A1
20060269165	Viswanathan	Nov 2006	A1
20060291719	Ikeda et al.	Dec 2006	A1
20070003154	Sun et al.	Jan 2007	A1
20070025612	Iwasaki et al.	Feb 2007	A1
20070031064	Zhao	Feb 2007	A1
20070063048	Havens et al.	Mar 2007	A1
20070116357	Dewaele	May 2007	A1
20070127022	Cohen et al.	Jun 2007	A1
20070143082	Degnan	Jun 2007	A1
20070153293	Gruhlke et al.	Jul 2007	A1
20070171220	Kriveshko	Jul 2007	A1
20070177011	Lewin et al.	Aug 2007	A1
20070181685	Zhu et al.	Aug 2007	A1
20070237356	Dwinell et al.	Oct 2007	A1
20070291031	Konev et al.	Dec 2007	A1
20070299338	Stevick et al.	Dec 2007	A1
20080013793	Hillis et al.	Jan 2008	A1
20080035390	Wurz	Feb 2008	A1
20080056536	Hildreth et al.	Mar 2008	A1
20080062164	Bassi et al.	Mar 2008	A1
20080077265	Boyden	Mar 2008	A1
20080079955	Storm	Apr 2008	A1
20080164074	Wurz	Jun 2008	A1
20080204476	Montague	Aug 2008	A1
20080212168	Olmstead et al.	Sep 2008	A1
20080247635	Davis et al.	Oct 2008	A1
20080273191	Kim et al.	Nov 2008	A1
20080273210	Hilde	Nov 2008	A1
20080278790	Boesser et al.	Nov 2008	A1
20090038182	Lans et al.	Feb 2009	A1
20090059004	Bochicchio	Mar 2009	A1
20090081008	Somin et al.	Mar 2009	A1
20090095047	Patel et al.	Apr 2009	A1
20090134221	Zhu et al.	May 2009	A1
20090195790	Zhu et al.	Aug 2009	A1
20090225333	Bendall et al.	Sep 2009	A1
20090237411	Gossweiler et al.	Sep 2009	A1
20090268023	Hsieh	Oct 2009	A1
20090272724	Gubler	Nov 2009	A1
20090273770	Bauhahn et al.	Nov 2009	A1
20090313948	Buckley et al.	Dec 2009	A1
20090318815	Barnes et al.	Dec 2009	A1
20090323084	Dunn et al.	Dec 2009	A1
20090323121	Valkenburg	Dec 2009	A1
20100035637	Varanasi et al.	Feb 2010	A1
20100060604	Zwart et al.	Mar 2010	A1
20100091104	Sprigle	Apr 2010	A1
20100113153	Yen et al.	May 2010	A1
20100118200	Gelman et al.	May 2010	A1
20100128109	Banks	May 2010	A1
20100161170	Siris	Jun 2010	A1
20100171740	Andersen et al.	Jul 2010	A1
20100172567	Prokoski	Jul 2010	A1
20100177076	Essinger et al.	Jul 2010	A1
20100177080	Essinger et al.	Jul 2010	A1
20100177707	Essinger et al.	Jul 2010	A1
20100177749	Essinger et al.	Jul 2010	A1
20100202702	Benos et al.	Aug 2010	A1
20100208039	Stettner	Aug 2010	A1
20100211355	Horst et al.	Aug 2010	A1
20100217678	Goncalves	Aug 2010	A1
20100220849	Colbert et al.	Sep 2010	A1
20100220894	Ackley et al.	Sep 2010	A1
20100223276	Al-Shameri et al.	Sep 2010	A1
20100245850	Lee et al.	Sep 2010	A1
20100254611	Amz	Oct 2010	A1
20100274728	Kugelman	Oct 2010	A1
20100303336	Abraham	Dec 2010	A1
20100315413	Izadi et al.	Dec 2010	A1
20100321482	Cleveland	Dec 2010	A1
20110019155	Daniel et al.	Jan 2011	A1
20110040192	Brenner et al.	Feb 2011	A1
20110043609	Choi et al.	Feb 2011	A1
20110099474	Grossman et al.	Apr 2011	A1
20110169999	Grunow et al.	Jul 2011	A1
20110188054	Petronius et al.	Aug 2011	A1
20110188741	Sones et al.	Aug 2011	A1
20110202554	Powilleit et al.	Aug 2011	A1
20110234389	Mellin	Sep 2011	A1
20110235854	Berger et al.	Sep 2011	A1
20110249864	Venkatesan et al.	Oct 2011	A1
20110254840	Halstead	Oct 2011	A1
20110260965	Kim et al.	Oct 2011	A1
20110279916	Brown et al.	Nov 2011	A1
20110286007	Pangrazio et al.	Nov 2011	A1
20110286628	Goncalves et al.	Nov 2011	A1
20110288818	Thierman	Nov 2011	A1
20110301994	Tieman	Dec 2011	A1
20110303748	Lemma et al.	Dec 2011	A1
20110310227	Konertz et al.	Dec 2011	A1
20120024952	Chen	Feb 2012	A1
20120056982	Katz et al.	Mar 2012	A1
20120057345	Kuchibhotla	Mar 2012	A1
20120067955	Rowe	Mar 2012	A1
20120074227	Ferren et al.	Mar 2012	A1
20120081714	Pangrazio et al.	Apr 2012	A1
20120111946	Golant	May 2012	A1
20120113223	Hilliges et al.	May 2012	A1
20120126000	Kunzig et al.	May 2012	A1
20120140300	Freeman	Jun 2012	A1
20120168512	Kotlarsky et al.	Jul 2012	A1
20120179665	Baarman et al.	Jul 2012	A1
20120185094	Rosenstein et al.	Jul 2012	A1
20120190386	Anderson	Jul 2012	A1
20120193423	Samek	Aug 2012	A1
20120197464	Wang et al.	Aug 2012	A1
20120203647	Smith	Aug 2012	A1
20120218436	Rodriguez et al.	Sep 2012	A1
20120223141	Good et al.	Sep 2012	A1
20120224026	Bayer et al.	Sep 2012	A1
20120224060	Gurevich et al.	Sep 2012	A1
20120236288	Stanley	Sep 2012	A1
20120242852	Hayward et al.	Sep 2012	A1
20120113250	Farlotti et al.	Oct 2012	A1
20120256901	Bendall	Oct 2012	A1
20120261474	Kawashime et al.	Oct 2012	A1
20120262558	Boger et al.	Oct 2012	A1
20120280908	Rhoads et al.	Nov 2012	A1
20120282905	Owen	Nov 2012	A1
20120282911	Davis et al.	Nov 2012	A1
20120284012	Rodriguez et al.	Nov 2012	A1
20120284122	Brandis	Nov 2012	A1
20120284339	Rodriguez	Nov 2012	A1
20120284593	Rodriguez	Nov 2012	A1
20120293610	Doepke et al.	Nov 2012	A1
20120293625	Schneider et al.	Nov 2012	A1
20120294549	Doepke	Nov 2012	A1
20120299961	Ramkumar et al.	Nov 2012	A1
20120300991	Mikio	Nov 2012	A1
20120313848	Galor et al.	Dec 2012	A1
20120314030	Datta	Dec 2012	A1
20120314058	Bendall et al.	Dec 2012	A1
20120316820	Nakazato et al.	Dec 2012	A1
20130019278	Sun et al.	Jan 2013	A1
20130038881	Pesach et al.	Feb 2013	A1
20130038941	Pesach et al.	Feb 2013	A1
20130043312	Van Horn	Feb 2013	A1
20130050426	Sarmast et al.	Feb 2013	A1
20130075168	Amundsen et al.	Mar 2013	A1
20130093895	Palmer et al.	Apr 2013	A1
20130094069	Lee et al.	Apr 2013	A1
20130101158	Lloyd et al.	Apr 2013	A1
20130156267	Muraoka et al.	Jun 2013	A1
20130175341	Kearney et al.	Jul 2013	A1
20130175343	Good	Jul 2013	A1
20130200150	Reynolds et al.	Aug 2013	A1
20130201288	Billerbaeck et al.	Aug 2013	A1
20130208164	Cazier et al.	Aug 2013	A1
20130211790	Loveland et al.	Aug 2013	A1
20130222592	Gieseke	Aug 2013	A1
20130223673	Davis et al.	Aug 2013	A1
20130257744	Daghigh et al.	Oct 2013	A1
20130257759	Daghigh	Oct 2013	A1
20130270346	Xian et al.	Oct 2013	A1
20130287258	Kearney	Oct 2013	A1
20130291998	Konnerth	Nov 2013	A1
20130292475	Kotlarsky et al.	Nov 2013	A1
20130292477	Hennick et al.	Nov 2013	A1
20130293539	Hunt et al.	Nov 2013	A1
20130293540	Laffargue et al.	Nov 2013	A1
20130306728	Thuries et al.	Nov 2013	A1
20130306731	Pedraro	Nov 2013	A1
20130307964	Bremer et al.	Nov 2013	A1
20130308013	Li et al.	Nov 2013	A1
20130308625	Park et al.	Nov 2013	A1
20130313324	Koziol et al.	Nov 2013	A1
20130313325	Wilz et al.	Nov 2013	A1
20130329012	Bartos	Dec 2013	A1
20130329013	Metois et al.	Dec 2013	A1
20130342342	Sabre et al.	Dec 2013	A1
20130342717	Havens et al.	Dec 2013	A1
20140001267	Giordano et al.	Jan 2014	A1
20140002828	Laffargue et al.	Jan 2014	A1
20140008439	Wang	Jan 2014	A1
20140009586	McNamer et al.	Jan 2014	A1
20140019005	Lee et al.	Jan 2014	A1
20140021259	Moed et al.	Jan 2014	A1
20140025584	Liu et al.	Jan 2014	A1
20140031665	Pinto et al.	Jan 2014	A1
20140034731	Gao et al.	Feb 2014	A1
20140034734	Sauerwein	Feb 2014	A1
20140036848	Pease et al.	Feb 2014	A1
20140039674	Motoyama et al.	Feb 2014	A1
20140039693	Havens et al.	Feb 2014	A1
20140042814	Kather et al.	Feb 2014	A1
20140049120	Kohtz et al.	Feb 2014	A1
20140049635	Laffargue et al.	Feb 2014	A1
20140058612	Wong et al.	Feb 2014	A1
20140061306	Wu et al.	Mar 2014	A1
20140062709	Hyer et al.	Mar 2014	A1
20140063289	Hussey et al.	Mar 2014	A1
20140064624	Kim et al.	Mar 2014	A1
20140066136	Sauerwein et al.	Mar 2014	A1
20140067104	Osterhout	Mar 2014	A1
20140067692	Ye et al.	Mar 2014	A1
20140070005	Nahill et al.	Mar 2014	A1
20140071430	Hansen et al.	Mar 2014	A1
20140071840	Venancio	Mar 2014	A1
20140074746	Wang	Mar 2014	A1
20140076974	Havens et al.	Mar 2014	A1
20140078341	Havens et al.	Mar 2014	A1
20140078342	Li et al.	Mar 2014	A1
20140078345	Showering	Mar 2014	A1
20140079297	Tadayon et al.	Mar 2014	A1
20140091147	Evans et al.	Apr 2014	A1
20140097238	Ghazizadeh	Apr 2014	A1
20140098091	Hori	Apr 2014	A1
20140098792	Wang et al.	Apr 2014	A1
20140100774	Showering	Apr 2014	A1
20140100813	Showering	Apr 2014	A1
20140103115	Meier et al.	Apr 2014	A1
20140104413	McCloskey et al.	Apr 2014	A1
20140104414	McCloskey et al.	Apr 2014	A1
20140104416	Giordano et al.	Apr 2014	A1
20140104451	Todeschini et al.	Apr 2014	A1
20140104664	Lee	Apr 2014	A1
20140106594	Skvoretz	Apr 2014	A1
20140106725	Sauerwein	Apr 2014	A1
20140108010	Maltseff et al.	Apr 2014	A1
20140108402	Gomez et al.	Apr 2014	A1
20140108682	Caballero	Apr 2014	A1
20140110485	Toa et al.	Apr 2014	A1
20140114530	Fitch et al.	Apr 2014	A1
20140124577	Wang et al.	May 2014	A1
20140124579	Ding	May 2014	A1
20140125842	Winegar	May 2014	A1
20140125853	Wang	May 2014	A1
20140125999	Longacre et al.	May 2014	A1
20140129378	Richardson	May 2014	A1
20140131438	Kearney	May 2014	A1
20140131441	Nahill et al.	May 2014	A1
20140131443	Smith	May 2014	A1
20140131444	Wang	May 2014	A1
20140131445	Ding et al.	May 2014	A1
20140131448	Xian et al.	May 2014	A1
20140133379	Wang et al.	May 2014	A1
20140135984	Hirata	May 2014	A1
20140136208	Maltseff et al.	May 2014	A1
20140139654	Takahashi	May 2014	A1
20140140585	Wang	May 2014	A1
20140142398	Patil et al.	May 2014	A1
20140151453	Meier et al.	Jun 2014	A1
20140152882	Samek et al.	Jun 2014	A1
20140152975	Ko	Jun 2014	A1
20140158468	Adami	Jun 2014	A1
20140158770	Sevier et al.	Jun 2014	A1
20140159869	Lumsteg et al.	Jun 2014	A1
20140166755	Liu et al.	Jun 2014	A1
20140166757	Smith	Jun 2014	A1
20140166759	Liu et al.	Jun 2014	A1
20140168380	Heidemann et al.	Jun 2014	A1
20140168787	Wang et al.	Jun 2014	A1
20140175165	Havens et al.	Jun 2014	A1
20140175172	Jovanovski et al.	Jun 2014	A1
20140177931	Kocherscheidt et al.	Jun 2014	A1
20140191644	Chaney	Jul 2014	A1
20140191913	Ge et al.	Jul 2014	A1
20140192187	Atwell et al.	Jul 2014	A1
20140192551	Masaki	Jul 2014	A1
20140197238	Lui et al.	Jul 2014	A1
20140197239	Havens et al.	Jul 2014	A1
20140197304	Feng et al.	Jul 2014	A1
20140201126	Zadeh et al.	Jul 2014	A1
20140203087	Smith et al.	Jul 2014	A1
20140204268	Grunow et al.	Jul 2014	A1
20140205150	Ogawa	Jul 2014	A1
20140214631	Hansen	Jul 2014	A1
20140217166	Berthiaume et al.	Aug 2014	A1
20140217180	Liu	Aug 2014	A1
20140225918	Mittal et al.	Aug 2014	A1
20140225985	Klusza et al.	Aug 2014	A1
20140231500	Ehrhart et al.	Aug 2014	A1
20140232930	Anderson	Aug 2014	A1
20140240454	Lee	Aug 2014	A1
20140247279	Nicholas et al.	Sep 2014	A1
20140247280	Nicholas et al.	Sep 2014	A1
20140247315	Marty et al.	Sep 2014	A1
20140263493	Amurgis et al.	Sep 2014	A1
20140263645	Smith et al.	Sep 2014	A1
20140267609	Laffargue	Sep 2014	A1
20140268093	Tohme et al.	Sep 2014	A1
20140270196	Braho et al.	Sep 2014	A1
20140270229	Braho	Sep 2014	A1
20140270361	Amma et al.	Sep 2014	A1
20140278387	DiGregorio	Sep 2014	A1
20140282210	Bianconi	Sep 2014	A1
20140284384	Lu et al.	Sep 2014	A1
20140288933	Braho et al.	Sep 2014	A1
20140297058	Barker et al.	Oct 2014	A1
20140299665	Barber et al.	Oct 2014	A1
20140306833	Ricci	Oct 2014	A1
20140307855	Withagen et al.	Oct 2014	A1
20140312121	Lu et al.	Oct 2014	A1
20140313527	Askan	Oct 2014	A1
20140319219	Liu et al.	Oct 2014	A1
20140319220	Coyle	Oct 2014	A1
20140319221	Oberpriller et al.	Oct 2014	A1
20140320408	Zagorsek et al.	Oct 2014	A1
20140326787	Barten	Nov 2014	A1
20140332590	Wang et al.	Nov 2014	A1
20140333775	Naikal et al.	Nov 2014	A1
20140344943	Todeschini et al.	Nov 2014	A1
20140346233	Liu et al.	Nov 2014	A1
20140347533	Ovsiannikov et al.	Nov 2014	A1
20140350710	Gopalkrishnan et al.	Nov 2014	A1
20140351317	Smith et al.	Nov 2014	A1
20140353373	Van Horn et al.	Dec 2014	A1
20140361073	Qu et al.	Dec 2014	A1
20140361082	Xian et al.	Dec 2014	A1
20140362184	Jovanovski et al.	Dec 2014	A1
20140363015	Braho	Dec 2014	A1
20140369511	Sheerin et al.	Dec 2014	A1
20140374483	Lu	Dec 2014	A1
20140374485	Xian et al.	Dec 2014	A1
20140379613	Nishitani et al.	Dec 2014	A1
20150001301	Ouyang	Jan 2015	A1
20150001304	Todeschini	Jan 2015	A1
20150003673	Fletcher	Jan 2015	A1
20150009100	Haneda et al.	Jan 2015	A1
20150009301	Ribnick et al.	Jan 2015	A1
20150009338	Laffargue et al.	Jan 2015	A1
20150009610	London et al.	Jan 2015	A1
20150014416	Kotlarsky et al.	Jan 2015	A1
20150021397	Rueblinger et al.	Jan 2015	A1
20150028102	Ren et al.	Jan 2015	A1
20150028103	Jiang	Jan 2015	A1
20150028104	Ma et al.	Jan 2015	A1
20150029002	Yeakley et al.	Jan 2015	A1
20150032709	Maloy et al.	Jan 2015	A1
20150036876	Marrion et al.	Feb 2015	A1
20150039309	Braho et al.	Feb 2015	A1
20150040378	Saber et al.	Feb 2015	A1
20150042791	Metois et al.	Feb 2015	A1
20150048168	Fritz et al.	Feb 2015	A1
20150049347	Laffargue et al.	Feb 2015	A1
20150051992	Smith	Feb 2015	A1
20150053766	Havens et al.	Feb 2015	A1
20150053768	Wang et al.	Feb 2015	A1
20150053769	Thuries et al.	Feb 2015	A1
20150062160	Sakamoto et al.	Mar 2015	A1
20150062366	Liu et al.	Mar 2015	A1
20150062369	Gehring et al.	Mar 2015	A1
20150063215	Wang	Mar 2015	A1
20150063676	Lloyd et al.	Mar 2015	A1
20150069130	Gannon	Mar 2015	A1
20150070158	Hayasaka	Mar 2015	A1
20150071819	Todeschini	Mar 2015	A1
20150083800	Li et al.	Mar 2015	A1
20150086114	Todeschini	Mar 2015	A1
20150088522	Hendrickson et al.	Mar 2015	A1
20150096872	Woodburn	Apr 2015	A1
20150099557	Pettinelli et al.	Apr 2015	A1
20150100196	Hollifield	Apr 2015	A1
20150102109	Huck	Apr 2015	A1
20150115035	Meier et al.	Apr 2015	A1
20150116498	Vartiainen et al.	Apr 2015	A1
20150117749	Chen et al.	Apr 2015	A1
20150127791	Kosecki et al.	May 2015	A1
20150128116	Chen et al.	May 2015	A1
20150129659	Feng et al.	May 2015	A1
20150133047	Smith et al.	May 2015	A1
20150134470	Hejl et al.	May 2015	A1
20150136851	Harding et al.	May 2015	A1
20150136854	Lu et al.	May 2015	A1
20150142492	Kumar	May 2015	A1
20150144692	Hejl	May 2015	A1
20150144698	Teng et al.	May 2015	A1
20150144701	Xian et al.	May 2015	A1
20150149946	Benos et al.	May 2015	A1
20150161429	Xian	Jun 2015	A1
20150163474	You	Jun 2015	A1
20150169925	Chen et al.	Jun 2015	A1
20150169929	Williams et al.	Jun 2015	A1
20150178900	Kim et al.	Jun 2015	A1
20150182844	Jang	Jul 2015	A1
20150186703	Chen et al.	Jul 2015	A1
20150193644	Kearney et al.	Jul 2015	A1
20150193645	Colavito et al.	Jul 2015	A1
20150199957	Funyak et al.	Jul 2015	A1
20150204662	Kobayashi et al.	Jul 2015	A1
20150204671	Showering	Jul 2015	A1
20150210199	Payne	Jul 2015	A1
20150213647	Laffargue et al.	Jul 2015	A1
20150219748	Hyatt	Aug 2015	A1
20150220753	Zhu et al.	Aug 2015	A1
20150229838	Hakim et al.	Aug 2015	A1
20150254485	Feng et al.	Sep 2015	A1
20150269403	Lei et al.	Sep 2015	A1
20150201181	Herschbach	Oct 2015	A1
20150276379	Ni et al.	Oct 2015	A1
20150308816	Laffargue et al.	Oct 2015	A1
20150316368	Moench et al.	Nov 2015	A1
20150325036	Lee	Nov 2015	A1
20150327012	Bian et al.	Nov 2015	A1
20150332463	Galera et al.	Nov 2015	A1
20150355470	Herschbach	Dec 2015	A1
20160014251	Hejl	Jan 2016	A1
20160169665	Deschenes et al.	Jan 2016	A1
20160040982	Li et al.	Feb 2016	A1
20160042241	Todeschini	Feb 2016	A1
20160048725	Holz et al.	Feb 2016	A1
20160057230	Todeschini et al.	Feb 2016	A1
20160070982	Li et al.	Feb 2016	A1
20160063429	Varley et al.	Mar 2016	A1
20160088287	Sadi et al.	Mar 2016	A1
20160090283	Svensson et al.	Mar 2016	A1
20160090284	Svensson et al.	Mar 2016	A1
20160101936	Chamberlin	Apr 2016	A1
20160102975	McCloskey et al.	Apr 2016	A1
20160104019	Todeschini et al.	Apr 2016	A1
20160104274	Jovanovski et al.	Apr 2016	A1
20160109219	Ackley et al.	Apr 2016	A1
20160109220	Laffargue et al.	Apr 2016	A1
20160109224	Thuries et al.	Apr 2016	A1
20160112631	Ackley et al.	Apr 2016	A1
20160112643	Laffargue et al.	Apr 2016	A1
20160124516	Schoon et al.	May 2016	A1
20160125217	Todeschini	May 2016	A1
20160125342	Miller et al.	May 2016	A1
20160133253	Braho et al.	May 2016	A1
20160138247	Conway et al.	May 2016	A1
20160138248	Conway et al.	May 2016	A1
20160138249	Svensson et al.	May 2016	A1
20160171720	Todeschini	Jun 2016	A1
20160178479	Goldsmith	Jun 2016	A1
20160180678	Ackley et al.	Jun 2016	A1
20160187186	Coleman et al.	Jun 2016	A1
20160187187	Coleman et al.	Jun 2016	A1
20160187210	Coleman et al.	Jun 2016	A1
20160189087	Morton et al.	Jun 2016	A1
20160191801	Sivan	Jun 2016	A1
20160125873	Braho et al.	Jul 2016	A1
20160202478	Masson	Jul 2016	A1
20160203641	Bostick et al.	Jul 2016	A1
20160223474	Tang et al.	Aug 2016	A1
20160227912	Oberpriller et al.	Aug 2016	A1
20160232891	Pecorari	Aug 2016	A1
20160292477	Bidwell	Oct 2016	A1
20160294779	Yeakley et al.	Oct 2016	A1
20160306769	Kohtz et al.	Oct 2016	A1
20160314276	Sewell et al.	Oct 2016	A1
20160314294	Kubler et al.	Oct 2016	A1
20160343176	Ackley	Nov 2016	A1
20170115490	Hsieh et al.	Apr 2017	A1
20170121158	Wong	May 2017	A1
20170182942	Hardy et al.	Jun 2017	A1

Foreign Referenced Citations (58)

Number	Date	Country
2004212587	Apr 2005	AU
201139117	Oct 2008	CN
3335760	Apr 1985	DE
10210813	Oct 2003	DE
102007037282	Mar 2008	DE
1111435	Jun 2001	EP
1443312	Aug 2004	EP
2013117	Jan 2009	EP
2286932	Feb 2011	EP
2372648	Oct 2011	EP
2381421	Oct 2011	EP
2533009	Dec 2012	EP
2562715	Feb 2013	EP
2722656	Apr 2014	EP
2779027	Sep 2014	EP
2833323	Feb 2015	EP
2843590	Mar 2015	EP
2845170	Mar 2015	EP
2966595	Jan 2016	EP
3006893	Mar 2016	EP
3012601	Mar 2016	EP
3007096	Apr 2016	EP
2503978	Jan 2014	GB
2525053	Oct 2015	GB
2531928	May 2016	GB
H04129902	Apr 1992	JP
200696457	Apr 2006	JP
2007084162	Apr 2007	JP
2008210276	Sep 2008	JP
2014210646	Nov 2014	JP
2015174705	Oct 2015	JP
20100020115	Feb 2010	KR
20110013200	Feb 2011	KR
20110117020	Oct 2011	KR
20120028109	Mar 2012	KR
9640452	Dec 1996	WO
0077726	Dec 2000	WO
0114836	Mar 2001	WO
2006095110	Sep 2006	WO
2007015059	Feb 2007	WO
200712554	Nov 2007	WO
2011017241	Feb 2011	WO
2012175731	Dec 2012	WO
2013021157	Feb 2013	WO
2013033442	Mar 2013	WO
2013163789	Nov 2013	WO
2013166368	Nov 2013	WO
2013173985	Nov 2013	WO
20130184340	Dec 2013	WO
2014019130	Feb 2014	WO
2014023697	Feb 2014	WO
2014102341	Jul 2014	WO
2014110495	Jul 2014	WO
2014149702	Sep 2014	WO
2014151746	Sep 2014	WO
2015006865	Jan 2015	WO
2016020038	Feb 2016	WO
2016061699	Apr 2016	WO

Non-Patent Literature Citations (128)

Entry
Thorlabs, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, downloaded from https://www.thorlabs.com/newgrouppage9.cfm?objectgroup_id=6430, 4 pages.
EKSMA Optics, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, downloaded from http://eksmaoptics.com/optical-systems/f-theta-lenses/f-theta-lens-for-1064-nm/, 2 pages.
Sill Optics, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, http://www.silloptics.de/1/products/sill-encyclopedia/laser-optics/f-theta-lenses/, 4 pages.
Chinese Notice of Reexamination in related Chinese Application 201520810313.3, dated Mar. 14, 2017, English Computer Translation provided, 7 pages.
Extended European search report in related EP Application 16199707.7, dated Apr. 10, 2017, 15 pages.
Ulusoy et al., One-Shot Scanning using De Bruijn Spaced Grids, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 7 pages [Cited in EP Extended search report dated Apr. 10, 2017].
European Examination report in related EP Application No. 14181437.6, dated Feb. 8, 2017, 5 pages.
Wikipedia, “Microlens”, Downloaded from https://en.wikipedia.org/wiki/Microlens, pp. 3. {Cited by Examiner in Feb. 9, 2017 Final Office Action in related matter}.
Fukaya et al., “Characteristics of Speckle Random Pattern and Its Applications”, pp. 317-327, Nouv. Rev. Optique, t.6, n.6. (1975) {Cited by Examiner in Feb. 9, 2017 Final Office Action in related matter: downloaded Mar. 2, 2017 from http://iopscience.iop.org}.
European Extended Search Report in related EP Application No. 16190017.0, dated Jan. 4, 2017, 6 pages.
European Extended Search Report in related EP Application No. 16173429.8, dated Dec. 1, 2016, 8 pages. [Only new references cited: US 2013/0038881 was previously cited].
Extended European Search Report in related EP Application No. 16175410.0, dated Dec. 13, 2016, 5 pages.
Peter Clarke, Actuator Developer Claims Anti-Shake Breakthrough for Smartphone Cams, Electronic Engineering Times, p. 24, May 16, 2011.
Spiller, Jonathan; Object Localization Using Deformable Templates, Master's Dissertation, University of the Witwatersrand, Johannesburg, South Africa, 2007; 74 pages.
Leotta, Matthew J.; Joseph L. Mundy; Predicting High Resolution Image Edges with a Generic, Adaptive, 3-D Vehicle Model; IEEE Conference on Computer Vision and Pattern Recognition, 2009; 8 pages.
European Search Report for application No. EP13186043 dated Feb. 26, 2014 (now EP2722656 (dated Apr. 23, 2014)): Total pp. 7.
European Patent Office Action for Application No. 14157971.4-1906, dated Jul. 16, 2014, 5 pages.
European Patent Search Report for Application No. 14157971.4-1906, dated Jun. 30, 2014, 6 pages.
Caulier, Yannick et al., “A New Type of Color-Coded Light Structures for an Adapted and Rapid Determination of Point Correspondences for 3D Reconstruction.” Proc. of SPIE, vol. 8082 808232-3; 2011; 8 pages.
Kazantsev, Aleksei et al. “Robust Pseudo-Random Coded Colored STructured Light Techniques for 3D Object Model Recovery”; ROSE 2008 IEEE International Workshop on Robotic and Sensors Environments (Oct. 17-18, 2008) , 6 pages.
Mouaddib E. et al. “Recent Progress in Structured Light in order to Solve the Correspondence Problem in Stereo Vision” Proceedings of the 1997 IEEE International Conference on Robotics and Automation, Apr. 1997; 7 pages.
Proesmans, Marc et al. “Active Acquisition of 3D Shape for Moving Objects” 0-7803-3258-X/96 1996 IEEE; 4 pages.
Salvi, Joaquim et al. “Pattern Codification Strategies in Structured Light Systems” published in Pattern Recognition; The Journal of the Pattern Recognition Society, Received Mar. 6, 2003; Accepted Oct. 2, 2003; 23 pages.
EP Search and Written Opinion Report in related matter EP Application No. 14181437.6, dated Mar. 26, 2015, 7 pages.
Hetzel, Gunter et al.; “3D Object Recognition from Range Images using Local Feature Histograms,”, Proceedings 2001 IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2001. Kauai, Hawaii, Dec. 8-14, 2001; pp. 394-399, XP010584149, ISBN: 978-0-7695-1272-3.
Second Chinese Office Action in related CN Application No. 201520810685.6, dated Mar. 22, 2016, 5 pages, no references.
European Search Report in related EP Application No. 15190315.0, dated Apr. 1, 2016, 7 pages.
International Search Report for PCT/US2013/039438 (WO2013166368), dated Oct. 1, 2013, 7 pages.
Lloyd, Ryan and Scott McCloskey, “Recognition of 3D Package Shapes for Singe Camera Metrology” IEEE Winter Conference on Applications of computer Visiona, IEEE, Mar. 24, 2014, pp. 99-106, {retrieved on Jun. 16, 2014}, Authors are employees of common Applicant.
European Office Action for application EP 13186043, dated Jun. 12, 2014(now EP2722656 (Apr. 23, 2014)), Total of 6 pages.
Zhang, Zhaoxiang; Tieniu Tan, Kaiqi Huang, Yunhong Wang; Three-Dimensional Deformable-Model-based Localization and Recognition of Road Vehicles; IEEE Transactions on Image Processing, vol. 21, No. 1, Jan. 2012, 13 pages.
U.S. Appl. No. 14/801,023, Tyler Doomenbal et al., filed Jul. 16, 2015, not published yet, Adjusting Dimensioning Results Using Augmented Reality, 39 pages.
Wikipedia, YUV description and definition, downloaded from http://www.wikipeida.org/wiki/YUV on Jun. 29, 2012, 10 pages.
YUV Pixel Format, downloaded from http://www.fource.org/yuv.php on Jun. 29, 2012; 13 pages.
YUV to RGB Conversion, downloaded from http://www.fource.org/fccyvrgb.php on Jun. 29, 2012; 5 pages.
Benos et al., “Semi-Automatic Dimensioning with Imager of a Portable Device,” U.S. Appl. No. 51/149,912, filed Feb. 4, 2009 (now expired), 56 pages.
Dimensional Weight—Wikipedia, the Free Encyclopedia, URL=http://en.wikipedia.org/wiki/Dimensional_weight, download date Aug. 1, 2008, 2 pages.
Dimensioning—Wikipedia, the Free Encyclopedia, URL=http://en.wikipedia.org/wiki/Dimensioning, download date Aug. 1, 2008, 1 page.
Decision to Grant in counterpart European Application No. 14157971.4 dated Aug. 6, 2015, pp. 1-2.
Leotta, Matthew, Generic, Deformable Models for 3-D Vehicle Surveillance, May 2010, Doctoral Dissertation, Brown University, Providence RI, 248 pages.
Ward, Benjamin, Interactive 3D Reconstruction from Video, Aug. 2012, Doctoral Thesis, Univesity of Adelaide, Adelaide, South Australia, 157 pages.
Hood, Frederick W.; William A. Hoff, Robert King, Evaluation of an Interactive Technique for Creating Site Models from Range Data, Apr. 27-May 1, 1997 Proceedings of the ANS 7th Topical Meeting on Robotics & Remote Systems, Augusta GA, 9 pages.
Gupta, Alok; Range Image Segmentation for 3-D Objects Recognition, May 1988, Technical Reports (CIS), Paper 736, University of Pennsylvania Department of Computer and Information Science, retrieved from Http://repository.upenn.edu/cis_reports/736, Accessed May 31, 2015, 157 pages.
Reisner-Kollmann,Irene; Anton L. Fuhrmann, Werner Purgathofer, Interactive Reconstruction of Industrial Sites Using Parametric Models, May 2010, Proceedings of the 26th Spring Conference of Computer Graphics SCCG 10, 8 pages.
Drummond, Tom; Roberto Cipolla, Real-Time Visual Tracking of Complex Structures, Jul. 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, No. 7; 15 pages.
European Search Report for Related EP Application No. 15189214.8, dated Mar. 3, 2016, 9 pages.
Santolaria et al. “A one-step intrinsic and extrinsic calibration method for laster line scanner operation in coordinate measuring machines”, dated Apr. 1, 2009, Measurement Science and Technology, IOP, Bristol, GB, vol. 20, No. 4; 12 pages.
Search Report and Opinion in Related EP Application 15176943.7, dated Jan. 8, 2016, 8 pages.
European Search Report for related EP Application No. 15188440.0, dated Mar. 8, 2016, 8 pages.
Second Chinese Office Action in related CN Application No. 2015220810562.2, dated Mar. 22, 2016, 5 pages. English Translation provided [No references].
European Search Report for related Application EP 15190249.1, dated Mar. 22, 2016, 7 pages.
Second Chinese Office Action in related CN Application No. 201520810313.3, dated Mar. 22, 2016, 5 pages. English Translation provided [No references].
U.S. Appl. No. 14/800,757 , Eric Todeschini, filed Jul. 16, 2015, not published yet, Dimensioning and Imaging Items, 80 pages.
U.S. Appl. No. 14/747,197, Serge Thuries et al., filed Jun. 23, 2015, not published yet, Optical Pattern Projector; 33 pages.
U.S. Appl. No. 14/747,490, Brian L. Jovanovski et al., filed Jun. 23, 2015, not published yet, Dual-Projector Three-Dimensional Scanner; 40 pages.
Search Report and Opinion in related GB Application No. 1517112.7, dated Feb. 19, 2016, 6 Pages.
U.S. Appl. No. 14/793,149, H. Sprague Ackley, filed Jul. 7, 2015, not published yet, Mobile Dimensioner Apparatus for Use in Commerce; 57 pages.
U.S. Appl. No. 14/740,373, H. Sprague Ackley et al., filed Jun. 16, 2015, not published yet, Calibrating a Volume Dimensioner; 63 pages.
Intention to Grant in counterpart European Application No. 14157971.4 dated Apr. 14, 2015, pp. 1-8.
United Kingdom Search Report in related application GB1517842.9, dated Apr. 8, 2016, 8 pages.
Great Britain Search Report for related Application On. GB1517843.7, dated Feb. 23, 2016; 8 pages.
U.S. Appl. No. 13/367,978, filed Feb. 7, 2012, (Feng et al.); now abandoned.
U.S. Appl. No. 14/277,337 for Multipurpose Optical Reader, filed May 14, 2014 (Jovanovski et al.); 59 pages; now abandoned.
U.S. Appl. No. 14/446,391 for Multifunction Point of Sale Apparatus With Optical Signature Capture filed Jul. 30, 2014 (Good et al.); 37 pages; now abandoned.
U.S. Appl. No. 29/516,892 for Table Computer filed Feb. 6, 2015 (Bidwell et al.); 13 pages.
U.S. Appl. No. 29/523,098 for Handle for a Tablet Computer filed Apr. 7, 2015 (Bidwell et al.); 17 pages.
U.S. Appl. No. 29/528,890 for Mobile Computer Housing filed Jun. 2, 2015 (Fitch et al.); 61 pages.
U.S. Appl. No. 29/526,918 for Charging Base filed May 14, 2015 (Fitch et al.); 10 pages.
U.S. Appl. No. 14/715,916 for Evaluating Image Values filed May 19, 2015 (Ackley); 60 pages.
U.S. Appl. No. 29/525,068 for Tablet Computer With Removable Scanning Device filed Apr. 27, 2015 (Schulte et al.); 19 pages.
U.S. Appl. No. 29/468,118 for an Electronic Device Case, filed Sep. 26, 2013 (Oberpriller et al.); 44 pages.
U.S. Appl. No. 29/530,600 for Cyclone filed Jun. 18, 2015 (Vargo et al); 16 pages.
U.S. Appl. No. 14/707,123 for Application Independent DEX/UCS Interface filed May 8, 2015 (Pape); 47 pages.
U.S. Appl. No. 14/283,282 for Terminal Having Illumination and Focus Control filed May 21, 2014 (Liu et al.); 31 pages; now abandoned.
U.S. Appl. No. 14/705,407 for Method and System to Protect Software-Based Network-Connected Devices From Advanced Persistent Threat filed May 6, 2015 (Hussey et al.); 42 pages.
U.S. Appl. No. 14/704,050 for Intermediate Linear Positioning filed May 5, 2015 (Charpentier et al.); 60 pages.
U.S. Appl. No. 14/705,012 for Hands-Free Human Machine Interface Responsive to a Driver of a Vehicle filed May 6, 2015 (Fitch et al.); 44 pages.
U.S. Appl. No. 14/715,672 for Augumented Reality Enabled Hazard Display filed May 19, 2015 (Venkatesha et al.); 35 pages.
U.S. Appl. No. 14/735,717 for Indicia-Reading Systems Having an Interface With a User's Nervous System filed Jun. 10, 2015 (Todeschini); 39 pages.
U.S. Appl. No. 14/702,110 for System and Method for Regulating Barcode Data Injection Into a Running Application on a Smart Device filed May 1, 2015 (Todeschini et al.); 38 pages.
U.S. Appl. No. 14/747,197 for Optical Pattern Projector filed Jun. 23, 2015 (Thuries et al.); 33 pages.
U.S. Appl. No. 14/702,979 for Tracking Battery Conditions filed May 4, 2015 (Young et al.); 70 pages.
U.S. Appl. No. 29/529,441 for Indicia Reading Device filed Jun. 8, 2015 (Zhou et al.); 14 pages.
U.S. Appl. No. 14/747,490 for Dual-Projector Three-Dimensional Scanner filed Jun. 23, 2015 (Jovanovski et al.); 40 pages.
U.S. Appl. No. 14/740,320 for Tactile Switch Fora Mobile Electronic Device filed Jun. 16, 2015 (Barndringa); 38 pages.
U.S. Appl. No. 14/740,373 for Calibrating a Volume Dimensioner filed Jun. 16, 2015 (Ackley et al.); 63 pages.
European extended search report in related EP Application 16190833.0, dated Mar. 9, 2017, 8 pages [only new art has been cited; US Publication 2014/0034731 was previously cited].
United Kingdom Combined Search and Examination Report in related Application No. GB1620676.5, dated Mar. 8, 2017, 6 pages [References have been previously cited; WO2014/151746, WO2012/175731, US 2014/0313527, GB2503978].
European Exam Report in related , EP Application No. 16168216.6, dated Feb. 27, 2017, 5 pages, [References have been previously cited; WO2011/017241 and US 2014/0104413].
Office Action in counterpart European Application No. 13186043.9 dated Sep. 30, 2015, pp. 1-7.
Lloyd et al., “System for Monitoring the Condition of Packages Throughout Transit”, U.S. Appl. No. 14/865,575, filed Sep. 25, 2015, 59 pages, not yet published.
McCloskey et al., “Image Transformation for Indicia Reading,” U.S. Appl. No. 14/928,032, filed Oct. 30, 2015, 48 pages, not yet published.
Great Britain Combined Search and Examination Report in related Application GB1517842.9, dated Apr. 8, 2016, 8 pages.
Search Report in counterpart European Application No. 15182675.7, dated Dec. 4, 2015, 10 pages.
Wikipedia, “3D projection” Downloaded on Nov. 25, 2015 from www.wikipedia.com, 4 pages.
M.Zahid Gurbuz, Selim Akyokus, Ibrahim Emiroglu, Aysun Guran, An Efficient Algorithm for 3D Rectangular Box Packing, 2009, Applied Automatic Systems: Proceedings of Selected AAS 2009 Papers, pp. 131-134.
European Extended Search Report in Related EP Application No. 16172995.9, dated Aug. 22, 2016, 11 pages.
European Extended search report in related EP Application No. 15190306.9, dated Sep. 9, 2016, 15 pages.
Collings et al., “The Applications and Technology of Phase-Only Liquid Crystal on Silicon Devices”, Journal of Display Technology, IEEE Service Center, New, York, NY, US, vol. 7, No. 3, Mar. 1, 2011 (Mar. 1, 2011), pp. 112-119.
European extended Search report in related EP Application 13785171.3, dated Sep. 19, 2016, 8 pages.
El-Hakim et al., “Multicamera vision-based approach to flexible feature measurement for inspection and reverse engineering”, published in Optical Engineering, Society of Photo-Optical Instrumentation Engineers, vol. 32, No. 9, Sep. 1, 1993, 15 pages.
El-Hakim et al., “A Knowledge-based Edge/Object Measurement Technique”, Retrieved from the Internet: URL: https://www.researchgate.net/profile/Sabry_E1-Hakim/publication/44075058_A_Knowledge_Based_EdgeObject_Measurement_Technique/links/00b4953b5faa7d3304000000.pdf [retrieved on Jul. 15, 2016] dated Jan. 1, 1993, 9 pages.
H. Sprague Ackley, “Automatic Mode Switching in a Volume Dimensioner”, U.S. Appl. No. 15/182,636, filed Jun. 15, 2016, 53 pages, Not yet published.
Bosch Tool Corporation, “Operating/Safety Instruction for DLR 130”, Dated Feb. 2, 2009, 36 pages.
European Search Report for related EP Application No. 16152477.2, dated May 24, 2016, 8 pages.
Mike Stensvold, “get the Most Out of Variable Aperture Lenses”, published on www.OutdoorPhotogrpaher.com; dated Dec. 7, 2010; 4 pages, [As noted on search report retrieved from URL: http;//www.outdoorphotographer.com/gear/lenses/get-the-most-out-ofvariable-aperture-lenses.html on Feb. 9, 2016].
Houle et al., “Vehical Positioning and Object Avoidance”, U.S. Appl. No. 15/007,522 [not yet published], filed Jan. 27, 2016, 59 pages.
United Kingdom combined Search and Examination Report in related GB Application No. 1607394.2, dated Oct. 19, 2016, 7 pages.
European Search Report from related EP Application No. 16168216.6, dated Oct. 20, 2016, 8 pages.
Padzensky, Ron; “Augmera; Gesture Control”, Dated Apr. 18, 2015, 15 pages.
Grabowski, Ralph; “New Commands in AutoCADS 2010: Part 11 Smoothing 3D Mesh Objects” Dated 2011, 6 pages.
Theodoropoulos, Gabriel; “Using Gesture Recognizers to Handle Pinch, Rotate, Pan, Swipe, and Tap Gestures” dated Aug. 25, 2014, 34 pages.
European Exam Report in related EP Application No. 16152477.2, dated Jun. 20, 2017, 4 pages.
European Exam Report in related EP Applciation 16172995.9, dated Jul. 6, 2017, 9 pages.
United Kingdom Search Report in related Application No. GB1700338.5, dated Jun. 30, 2017, 5 pages.
European Search Report in related EP Application No. 17175357.7, dated Aug. 17, 2017, pp. 1-7.
Ralph Grabowski, “Smothing 3D Mesh Objects,” New Commands in AutoCAD 2010: Part 11, dated May 19, 2017; 6 pages.
European Exam Report in related EP Application No. 15176943.7, dated Apr. 12, 2017, 6 pages.
European Exam Report in related EP Application No. 15188440.0, dated Apr. 21, 2017, 4 pages.
Boavida et al., “Dam monitoring using combined terrestrial imaging systems”, 2009 Civil Engineering Survey Dec./Jan. 2009, pp. 33-38 {Notice of Allowance dated Sep. 15, 2017 in related matter}.
EP Search Report in related EP Application No. 17171844 dated Sep. 18, 2017. 4 pages.
EP Extended Search Report in related EP Applicaton No. 17174843.7 dated Oct. 17, 2017, 5 pages.
UK Further Exam Report in related UK Application No. GB1517842.9, dated Sep. 1, 2017, 5 pages.
Ulusoy, Ali Osman et al.; “One-Shot Scanning using De Bruijn Spaced Grids”, Brown University; 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pp. 1786-1792 [EPO Search Report dated Dec. 5, 2017].
Extended European Search report in related EP Application No. 17189496.7 dated Dec. 5, 2017; 9 pages.
Examination Report in related EP Application No. 15190315, dated Jan. 26, 2018, 6 pages.
Examination Report in related GB Application No. GB1517843.7, dated Jan. 19, 2018, 4 pages.
Extended European Search report in related EP Application No. 17190323.0 dated Jan. 19, 2018; 6 pages.

Related Publications (1)

	Number	Date	Country
	20170358098 A1	Dec 2017	US

Scene change detection in a dimensioner

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