Abstract: An image processor comprises image processing circuitry implementing a plurality of processing layers including a preprocessing layer for received image data and one or more higher processing layers coupled to the preprocessing layer. The image processor further comprises a multi-channel interface including at least first and second image data channels arranged in parallel with one another between the preprocessing layer and a given higher processing layer. The first image data channel is configured to carry partial depth information derived from the received image data to the given higher processing layer, and the second image data channel is configured to carry complete preprocessed frames of the received image data from the preprocessing layer to the given higher processing layer. By way of example only, in a given embodiment the partial depth information comprises depth information determined to have at least a specified level of reliability.

Abstract: In one embodiment, an image processor is configured to obtain a plurality of phase images for each of first and second depth frames. For each of a plurality of pixels of a given one of the phase images of the first depth frame, the image processor determines an amount of movement of a point of an imaged scene between the pixel of the given phase image and a pixel of a corresponding phase image of the second depth frame, and adjusts pixel values of respective other phase images of the first depth frame based on the determined amount of movement. A motion compensated first depth image is generated utilizing the given phase image and the adjusted other phase images of the first depth frame. Movement of a point of the imaged scene is determined, for example, between pixels of respective n-th phase images of the first and second depth frames.

Abstract: An image processing system comprises an image processor configured to obtain a first image stream having a first frame rate and a second image stream having a second frame rate lower than the first frame rate, to recover additional frames for the second image stream based on existing frames of the first and second image streams, and to utilize the additional frames to provide an increased frame rate for the second image stream. Recovering additional frames for the second image stream based on existing frames of the first and second image streams illustratively comprises determining sets of one or more additional frames for insertion between respective pairs of consecutive existing frames in the second image stream in respective iterations.

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 processing system comprises an image processor configured to perform first and second edge detection operations on respective first and second images to obtain respective first and second edge images, to apply a joint edge weighting operation using edges from the first and second edge images, to generate an edge mask based on results of the edge weighting operation, to utilize the edge mask to obtain a third edge image, and to generate a third image based on the third edge image. By way of example only, in a given embodiment the first image may comprise a first depth image generated by a depth imager, the second image may comprise a two-dimensional image of substantially the same scene as the first image, and the third image may comprise an enhanced depth image having enhanced edge quality relative to the first depth image.

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 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 configured to perform first and second edge detection operations on respective first and second images to obtain respective first and second edge images, to apply a joint edge weighting operation using edges from the first and second edge images, to generate an edge mask based on results of the edge weighting operation, to utilize the edge mask to obtain a third edge image, and to generate a third image based on the third edge image. By way of example only, in a given embodiment the first image may comprise a first depth image generated by a depth imager, the second image may comprise a two-dimensional image of substantially the same scene as the first image, and the third image may comprise an enhanced depth image having enhanced edge quality relative to the first depth 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 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: An image processing system comprises an image processor implemented using at least one processing device and adapted for coupling to an image source, such as a depth imager. The image processor is configured to compute a convergence matrix and a noise threshold matrix, to estimate background information of an image utilizing the convergence matrix, and to eliminate at least a portion of the background information from the image utilizing the noise threshold matrix. The background estimation and elimination may involve the generation of static and dynamic background masks that include elements indicating which pixels of the image are part of respective static and dynamic background information. The computing, estimating and eliminating operations may be performed over a sequence of depth images, such as frames of a 3D video signal, with the convergence and noise threshold matrices being recomputed for each of at least a subset of the 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.

Abstract: An image processing system comprises an image processor configured to obtain a first image stream having a first frame rate and a second image stream having a second frame rate lower than the first frame rate, to recover additional frames for the second image stream based on existing frames of the first and second image streams, and to utilize the additional frames to provide an increased frame rate for the second image stream. Recovering additional frames for the second image stream based on existing frames of the first and second image streams illustratively comprises determining sets of one or more additional frames for insertion between respective pairs of consecutive existing frames in the second image stream in respective iterations.