Abstract: The techniques described herein relate to methods, apparatus, and computer readable media configured to determining a candidate three-dimensional (3D) orientation of an object represented by a three-dimensional (3D) point cloud. The method includes receiving data indicative of a 3D point cloud comprising a plurality of 3D points, determining a first histogram for the plurality of 3D points based on geometric features determined based on the plurality of 3D points, accessing data indicative of a second histogram of geometric features of a 3D representation of a reference object, computing, for each of a plurality of different rotations between the first histogram and the second histogram in 3D space, a scoring metric for the associated rotation, and determining the candidate 3D orientation based on the scoring metrics of the plurality of different rotations.

Abstract: The techniques described herein relate to methods, apparatus, and computer readable media configured to generate point cloud histograms. A one-dimensional histogram can be generated by determining a distance to a reference for each 3D point of a 3D point cloud. A one-dimensional histogram is generated by adding, for each histogram entry, distances that are within the entry's range of distances. A two-dimensional histogram can be determined by generating a set of orientations by determining, for each 3D point, an orientation with at least a first value for a first component and a second value for a second component. A two-dimensional histogram can be generated based on the set of orientations. Each bin can be associated with ranges of values for the first and second components. Orientations can be added for each bin that have first and second values within the first and second ranges of values, respectively, of the bin.

Abstract: A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Abstract: A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Abstract: A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Abstract: The techniques described herein relate to methods, apparatus, and computer readable media configured to generate point cloud histograms. A one-dimensional histogram can be generated by determining a distance to a reference for each 3D point of a 3D point cloud. A one-dimensional histogram is generated by adding, for each histogram entry, distances that are within the entry's range of distances. A two-dimensional histogram can be determined by generating a set of orientations by determining, for each 3D point, an orientation with at least a first value for a first component and a second value for a second component. A two-dimensional histogram can be generated based on the set of orientations. Each bin can be associated with ranges of values for the first and second components. Orientations can be added for each bin that have first and second values within the first and second ranges of values, respectively, of the bin.

Abstract: A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Abstract: The techniques described herein relate to methods, apparatus, and computer readable media configured to generate point cloud histograms. A one-dimensional histogram can be generated by determining a distance to a reference for each 3D point of a 3D point cloud. A one-dimensional histogram is generated by adding, for each histogram entry, distances that are within the entry's range of distances. A two-dimensional histogram can be determined by generating a set of orientations by determining, for each 3D point, an orientation with at least a first value for a first component and a second value for a second component. A two-dimensional histogram can be generated based on the set of orientations. Each bin can be associated with ranges of values for the first and second components. Orientations can be added for each bin that have first and second values within the first and second ranges of values, respectively, of the bin.

Abstract: The techniques described herein relate to methods, apparatus, and computer readable media configured to generate point cloud histograms. A one-dimensional histogram can be generated by determining a distance to a reference for each 3D point of a 3D point cloud. A one-dimensional histogram is generated by adding, for each histogram entry, distances that are within the entry's range of distances. A two-dimensional histogram can be determined by generating a set of orientations by determining, for each 3D point, an orientation with at least a first value for a first component and a second value for a second component. A two-dimensional histogram can be generated based on the set of orientations. Each bin can be associated with ranges of values for the first and second components. Orientations can be added for each bin that have first and second values within the first and second ranges of values, respectively, of the bin.

Abstract: A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Abstract: An apparatus and method for providing automatic threat detection using passive millimeter wave detection and image processing analysis.

Abstract: Embodiments relate to appearance model based automatic detection in sensor images. In one arrangement, a detection apparatus of an Automated Threat Detection system utilizes generative, statistical models of human appearance in sensor images, such as MMW images, as a basis for comparison with images received by a sensor such as an MMW sensor. The detection apparatus can effectively replicate, through the models, the approach of human observers to provide a relatively high throughput of subjects. Additionally, by utilizing generative, statistical models as the basis for comparison against received MMW images, the detection apparatus can minimize detection errors caused by variance in body geometry, skin reflectance, and posture of the subject to maintain a relatively low rate of false alarms and a relatively high rate of detection of threats.

Abstract: An apparatus and method for providing automatic threat detection using passive millimeter wave detection and image processing analysis.

Abstract: An apparatus and method for providing automatic threat detection using passive millimeter wave detection and image processing analysis.

Abstract: An apparatus and method for providing automatic threat detection using passive millimeter wave detection and image processing analysis.

Abstract: A method for creating a novel viewpoint image from a plurality of images includes the steps of simultaneously and continuously acquiring sets of images from a plurality of cameras. Predetermined background based correspondence fields are used to detect novel objects. Image representations are assigned for these objects likely new correspondences. These likely new correspondences are tested and further improved upon in a refinement step. The resulting correspondences are used to construct a novel viewpoint image.

Abstract: Unpredictable response variations of the output value signals from radiometer or receiver channels due to noise are minimized when composing a millimeter wave image. The image is composed from composition signals which are each related to the corresponding output value signals from the channels. Some composition signals are weighted by a weighting factor which is different from a weighting factor used for weighting other composition signals. Preferably, the reciprocal of the standard deviation of variations of the output value signals from each channel is used as the weighting factor for deriving the composition signals from the output value signals from that channel. The intensity of each pixel of the image is composed by adding the weighted composition signals associated with that pixel.

Abstract: Output value signals from radiometer or receiver channels are normalized to achieve a flat field response when creating a millimeter wave image. A normalizing factor is applied to the output value signals from each channel, and the normalizing factor accommodates drift in offset of the output value signals on a scan-by-scan basis. The normalizing factor is based on each channel observing a different mean scan brightness temperature from a portion of the scene than the mean brightness temperature of the entire scene. The normalizing factor is obtained by solving a system of simultaneous equations in which normalizing factors from all of the channels are related to one another, preferably by a consistency condition where the mean scan temperature of each channel is equal to an average of the intensities of those image pixels to which the output value signals from that channel contributes.

Abstract: Scene-independent baseline signals in output value signals from radiometer or receiver channels used in millimeter wave imaging are eliminated or reduced and an improved image is composed. The scene-independent baseline signals are believed to result from a standing wave which is established between an antenna of the channel and a movable scanning element which scans radiant energy from the scene into each channel. The movable scanning element introduces changes in geometry which change the characteristics of the baseline signals depending upon the position of the movable scanning element. The baseline signals are measured by viewing a scene of uniform brightness temperature, and the baseline signal contribution is subtracted from the output value signals from each channel. The baseline compensated output signals are used to compose an image with better contrast.

Abstract: Output value signals from radiometer or receiver channels are normalized to achieve a flat field response when creating a millimeter wave image. A normalizing factor is applied to the output value signals from each channel, and the normalizing factor accommodates drift in offset of the output value signals on a scan-by-scan basis. The normalizing factor is based on each channel observing a different mean scan brightness temperature from a portion of the scene than the mean brightness temperature of the entire scene. The normalizing factor is obtained by solving a system of simultaneous equations in which normalizing factors from all of the channels are related to one another, preferably by a consistency condition where the mean scan temperature of each channel is equal to an average of the intensities of those image pixels to which the output value signals from that channel contributes.