Abstract: Systems and methods for image processing may perform one or more operations including, but not limited to: receiving raw image data from at least one imaging device; computing at least one image depth distance from the raw image data; computing one or more image validity flags from the raw image data; generating at least one data validity mask from the one or more image validity flags; determining a background imagery estimation from at least one image depth distance; generating at least one foreground mask from the background imagery estimation and the at least one image depth distance; generating at least one region-of-interest mask from the data validity mask and the foreground mask; and generating filtered raw image data from the raw image data and at least one region of interest mask.

Abstract: In one embodiment, an image processor comprises image processing circuitry and an associated memory. The image processor is configured to implement a gesture recognition system utilizing the image processing circuitry and the memory. The gesture recognition system implemented by the image processor comprises a dynamic gesture recognition module. The dynamic gesture recognition module is configured to establish a dynamic gesture recognition interval comprising a plurality of image frames, to extract one or more first features from the dynamic gesture recognition interval, to adjust the dynamic gesture recognition interval, to extract one or more second features from the adjusted dynamic gesture recognition interval, and to recognize a dynamic gesture based at least in part on at least a subset of the extracted first and second features.

Abstract: In one embodiment, an image processor is configured to obtain phase images, and to group the phase images into pseudoframes with each of at least a subset of the pseudoframes comprising multiple ones of the phase images and having as a first phase image thereof one of the phase images that is not a first phase image of an associated depth frame. A velocity field is estimated by comparing corresponding phase images in respective ones of the pseudoframes. Phase images of one or more pseudoframes are modified based at least in part on the estimated velocity field, and one or more depth images are generated based at least in part on the modified phase images. By way of example, different groupings of the phase images into pseudoframes may be used for each obtained phase image, allowing depth images to be generated at much higher rates than would otherwise be possible.

Abstract: Systems and methods for image processing may perform one or more operations including, but not limited to: receiving raw image data from at least one imaging device; computing at least one image depth distance from the raw image data; computing one or more image validity flags from the raw image data; generating at least one data validity mask from the one or more image validity flags; determining a background imagery estimation from at least one image depth distance; generating at least one foreground mask from the background imagery estimation and the at least one image depth distance; generating at least one region-of-interest mask from the data validity mask and the foreground mask; and generating filtered raw image data from the raw image data and at least one region of interest mask.

Abstract: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement an object tracking module. The object tracking module is configured to obtain one or more images, to extract contours of at least two objects in at least one of the images, to select respective subsets of points of the contours for the at least two objects based at least in part on curvatures of the respective contours, to calculate features of the subsets of points of the contours for the at least two objects, to detect intersection of the at least two objects in a given image, and to track the at least two objects in the given image based at least in part on the calculated features responsive to detecting intersection of the at least two objects in the given image.

Abstract: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement a gesture recognition system comprising a contour classification module. The contour classification module is configured to identify one or more hand poses from one or more isolated regions in a first image, to determine a contour of a given one of the one or more hand poses, to calculate one or more features of the contour of the given hand pose, to identify one or more isolated regions in a second image, and to determine whether at least a portion of one or more isolated regions in the second image matches the given hand pose based on a comparison of one or more points characterizing the portion of the one or more isolated regions in the second image and the one or more features of the contour of the given hand pose.

Abstract: The disclosure is directed to a system and method of image processing. According to various embodiments of the disclosure, a storage module in communication with a plurality of memory banks stores a plurality of pixels of an image in the memory banks and interleaves the memory banks to enable a plurality of image scanners to access the plurality of pixels. A scanning module scans a selection of pixels in at least four directions relative to a first pixel of the plurality of pixels utilizing the plurality of image scanners. A singular points detection module in communication with the scanning module acquires a depth of each pixel of the selection of scanned pixels and determines a singularity value of the first pixel by comparing the depth of the first pixel with the depth of each pixel of the selection of pixels.