Abstract: An image processing system comprises an image processor configured to construct a designated functional based on a plurality of functions each associated with a corresponding portion of image information relating to at least first and second images, and to generate a target image utilizing the constructed functional. For example, the functions may comprise a set of functions ƒ1(A1), ƒ1(A1), . . . , ƒ1(A1) of pixels from respective input images A1, A2, AL of the image information, and the functional may be a function F(X) of the set of functions ƒ1,(A1) ƒ2(AL), ƒL(AL) where X denotes the target image and is generated by minimizing the functional F(X). The input images may be received from one or more image sources and the target image may be provided to one or more image destinations.

Abstract: An image processing system comprises an image processor configured to identify edges in an image, to apply a first type of filtering operation to portions of the image associated with the edges, and to apply a second type of filtering operation to one or more other portions of the image. By way of example only, in a given embodiment a clustering operation is applied to the image to identify a plurality of clusters, a first set of edges comprising edges of the clusters is identified, an edge detection operation is applied to the image to identify a second set of edges, a third set of edges is identified based on the first and second sets of edges, and the first type of filtering operation is applied to portions of the image associated with one or more edges of the third set of edges.

Abstract: An image processor comprises image processing circuitry implementing a plurality of processing layers including at least an evaluation layer and a recognition layer. The evaluation layer comprises a software-implemented portion and a hardware-implemented portion, with the software-implemented portion of the evaluation layer being configured to generate first object data of a first precision level using a software algorithm, and the hardware-implemented portion of the evaluation layer being configured to generate second object data of a second precision level lower than the first precision level using a hardware algorithm. The evaluation layer further comprises a signal combiner configured to combine the first and second object data to generate output object data for delivery to the recognition layer. By way of example only, the evaluation layer may be implemented in the form of an evaluation subsystem of a gesture recognition system of the image processor.

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 static pose recognition module. The static pose recognition module is configured to identify a hand region of interest in at least one image, to extract a contour of the hand region of interest, to compute a feature vector based at least in part on the extracted contour, and to recognize a static pose of the hand region of interest utilizing a dynamic warping operation based at least in part on the feature vector.

Abstract: An image processing system comprises an image processor configured to identify edges in an image, to apply a first type of filtering operation to portions of the image associated with the edges, and to apply a second type of filtering operation to one or more other portions of the image. By way of example only, in a given embodiment a clustering operation is applied to the image to identify a plurality of clusters, a first set of edges comprising edges of the clusters is identified, an edge detection operation is applied to the image to identify a second set of edges, a third set of edges is identified based on the first and second sets of edges, and the first type of filtering operation is applied to portions of the image associated with one or more edges of the third set of edges.

Abstract: An image processor comprises image processing circuitry implementing a plurality of processing layers including at least an evaluation layer and a recognition layer. The evaluation layer comprises a software-implemented portion and a hardware-implemented portion, with the software-implemented portion of the evaluation layer being configured to generate first object data of a first precision level using a software algorithm, and the hardware-implemented portion of the evaluation layer being configured to eV generate second object data of a second precision level lower than the first precision level using a hardware algorithm. The evaluation layer further comprises a signal combiner configured to combine the first and second object data to generate output object data for delivery to the recognition layer. By way of example only, the evaluation layer may be implemented in the form of an evaluation subsystem of a gesture recognition system of the image processor.

Abstract: An image processing system comprises an image processor configured to construct a designated functional based on a plurality of functions each associated with a corresponding portion of image information relating to at least first and second images, and to generate a target image utilizing the constructed functional. For example, the functions may comprise a set of functions f1(A1), f1(A1), . . . , f1(A1) of pixels from respective input images A1, A2, AL of the image information, and the functional may be a function F(X) of the set of functions f1,(A1) f2(AL), fL(AL) where X denotes the target image and is generated by minimizing the functional F(X). The input images may be received from one or more image sources and the target image may be provided to one or more image destinations.

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. The gesture recognition system comprises a cursor detector, a dynamic gesture detector, a static pose recognition module, and a finite state machine configured to control selectively enabling of the cursor detector, the dynamic gesture detector and the static pose recognition module. By way of example, the finite state machine includes a cursor detected state in which cursor location and tracking are applied responsive to detection of a cursor in a current frame, a dynamic gesture detected state in which dynamic gesture recognition is applied responsive to detection of a dynamic gesture in the current frame, and a static pose recognition state in which static pose recognition is applied responsive to failure to detect a cursor or a dynamic gesture in the current frame.

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 static pose recognition module. The static pose recognition module is configured to identify a region of interest in at least one image, to represent the region of interest as a segmented region of interest comprising a union of segment sets from respective ones of a plurality of lines, to estimate features of the segmented region of interest, and to recognize a static pose of the segmented region of interest based on the estimated features. The lines from which the respective segment sets are taken illustratively comprise respective parallel lines configured as one of horizontal lines, vertical lines and rotated lines. A given one of the segments in one of the sets may be represented by a pair of segment coordinates.

Abstract: In one embodiment, an image processing system comprises an image processor configured to obtain depth and amplitude data associated with a depth image, to identify a region of interest based on the depth and amplitude data, to separately compress the depth and amplitude data based on the identified region of interest to form respective compressed depth and amplitude portions, and to combine the separately compressed portions to provide a compressed depth image. The image processor may additionally or alternatively be configured to obtain a compressed depth image, to divide the compressed depth image into compressed depth and amplitude portions, and to separately decompress the compressed depth and amplitude portions to provide respective depth and amplitude data associated with a depth image. Other embodiments of the invention can be adapted for compressing or decompressing only depth data associated with a given depth image or sequence of depth images.

Abstract: An image processing system comprises an image processor configured to identify a plurality of candidate boundaries in an image, to obtain corresponding modified images for respective ones of the candidate boundaries, to apply a mapping function to each of the modified images to generate a corresponding vector, to determine sets of estimates for respective ones of the vectors relative to designated class parameters, and to select a particular one of the candidate boundaries based on the sets of estimates. The designated class parameters may include sets of class parameters for respective ones of a plurality of classes each corresponding to a different gesture to be recognized. The candidate boundaries may comprise candidate palm boundaries associated with a hand in the image. The image processor may be further configured to select a particular one of the plurality of classes to recognize the corresponding gesture based on the sets of estimates.