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 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: An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to identify a region of interest in an amplitude image, to detect one or more relatively low gradient regions in the region of interest, to reconstruct depth information for said one or more relatively low gradient regions, to extend the reconstructed depth information beyond said one or more relatively low gradient regions to additional pixels of the region of interest, and to generate a depth image utilizing at least portions of the reconstructed depth information and the extended reconstructed depth information. The image processor in some embodiments is adapted for coupling to an active lighting image sensor, such as an infrared sensor that does not provide depth information corresponding to the amplitude image, or an SL or ToF sensor that provides depth information corresponding to the amplitude image.

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 perform an edge detection operation on a first image to obtain a second image, to identify particular edges of the second image that exhibit at least a specified reliability, and to generate a third image comprising the particular edges and excluding other edges of the second image. By way of example only, in a given embodiment the first image may comprise a depth image generated by a depth imager, the second image may comprise an edge image generated by applying the edge detection operation to the depth image, and the third image may comprise a modified edge image having only the particular edges that exhibit at least the specified reliability.

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 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 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: A depth imager is configured to generate a first depth image using a first depth imaging technique, and to generate a second depth image using a second depth imaging technique different than the first depth imaging technique. At least portions of the first and second depth images are merged to form a third depth image. The depth imager comprises at least one sensor including a single common sensor at least partially shared by the first and second depth imaging techniques, such that the first and second depth images are both generated at least in part using data acquired from the single common sensor. By way of example, the first depth image may comprise a structured light (SL) depth map generated using an SL depth imaging technique, and the second depth image may comprise a time of flight (ToF) depth map generated using a ToF depth imaging technique.

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 configured to determine velocity of a hand in a plurality of images, and to selectively enable dynamic gesture recognition for at least one image responsive to the determined velocity. By way of example, the image processor illustratively includes a dynamic gesture preprocessing detector and a dynamic gesture recognizer, with the dynamic gesture preprocessing detector being configured to determine the velocity of the hand for a current frame and to compare the determined velocity to a specified velocity threshold. If the determined velocity is greater than or equal to the velocity threshold, the dynamic gesture recognizer operates on the current frame, and otherwise the dynamic gesture recognizer is bypassed for the current frame. The dynamic gesture recognizer when enabled is configured to generate similarity measures for respective ones of a plurality of gestures of a gesture vocabulary for the current frame.

Abstract: An image processing system comprises an image processor configured to perform an edge detection operation on a first image to obtain a second image, to identify particular edges of the second image that exhibit at least a specified reliability, and to generate a third image comprising the particular edges and excluding other edges of the second image. By way of example only, in a given embodiment the first image may comprise a depth image generated by a depth imager, the second image may comprise an edge image generated by applying the edge detection operation to the depth image, and the third image may comprise a modified edge image having only the particular edges that exhibit at least the specified reliability.

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 hand region of interest in at least one image, to perform a skeletonization operation on the hand region of interest, to determine a main direction of the hand region of interest utilizing a result of the skeletonization operation, to perform a scanning operation on the hand region of interest utilizing the determined main direction to estimate a plurality of hand features that are substantially invariant to hand orientation, and to recognize a static pose of the hand region of interest based on the estimated hand features.

Abstract: An image processing system comprises an image processor configured to establish a main processing thread and a parallel processing thread for respective portions of a multithreaded gesture recognition process. The parallel processing thread is configured to utilize buffer circuitry of the image processor, such as one or more double buffers of the buffer circuitry, so as to permit the parallel processing thread to run asynchronously to the main processing thread. The parallel processing thread implements one of noise estimation, background estimation and static hand pose recognition for the multithreaded gesture recognition process. Additional processing threads may be established to run in parallel with the main processing thread. For example, the image processor may establish a first parallel processing thread implementing the noise estimation, a second parallel processing thread implementing the background estimation, and a third parallel processing thread implementing the static hand pose recognition.

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 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.