Abstract:
A point cloud encoder including an input interface to accept a dynamic point cloud including a sequence of point cloud frames of a scene. A processor encodes blocks of a current point cloud frame to produce an encoded frame. Wherein, for encoding a current block of the current point cloud frame, a reference block is selected similar to the current block according to a similarity metric to serve as a reference to encode the current block. Pair each point in the current block to a point in the reference block based on values of the paired points. Encode the current block based on a combination of an identification of the reference block and residuals between the values of the paired points. Wherein the residuals are ordered according to an order of the values of the points in the reference block. A transmitter transmits the encoded frame over a communication channel.
Abstract:
A method processes keypoint trajectories in a video, wherein the keypoint trajectories describe motion of a plurality of keypoints across pictures of the video over time, by first acquiring the video of a scene using a camera. Keypoints and associated feature descriptors are detected in each picture. The keypoints and associated features descriptors are matched between neighboring pictures to generate keypoint trajectories. Then, the keypoint trajectories are coded predictively into a bitstream, which is outputted.
Abstract:
A method processes a signal represented as a graph by first determining a graph spectral transform based on the graph. In a spectral domain, parameters of a graph filter are estimated using a training data set of unenhanced and corresponding enhanced signals. The graph filter is derived based on the graph spectral transform and the estimated graph filter parameters. Then, the signal is processed using the graph filter to produce an output signal. The processing can enhance signals such as images by denoising or interpolating missing samples.
Abstract:
A method reconstructs a signal by sampling the signal using a sampling procedure to obtain an input signal. A consistent set is determined from the input signal including the first elements such that applying the sampling procedure to the first elements results in the input signal. According to the type of the signal, a guiding set is determined including second elements disjoint from the first elements. A reconstruction set including third elements is generated so that the third elements minimize a sum of a first similarity measure of the third elements to the second elements and a second similarity measure of the third elements to the first elements. A transformed signal that minimizes a function on the reconstruction set is determined. A reconstructed signal is rendered so that a third similarity measure of the reconstructed signal to the transformed signal is smaller than a tolerance.
Abstract:
A method segments an image acquired by a sensor of a scene by first obtaining motion vectors corresponding to the image and generating a motion vanishing point image, wherein each pixel in the motion vanishing point image represents a number of intersections of pairs of motion vectors at the pixel. In the motion vanishing point image, a representation point for each motion vector is generated and distances between the motion vectors are determined based on the representation points. Then, a motion graph is constructed wherein each node represents a motion vector, and each edge represents a weight based on the distance between the nodes. Graph spectral clustering is performed on the motion graph to produce segments of the image.
Abstract:
A method reconstructs a signal by sampling the signal using a sampling procedure to obtain an input signal. A consistent set is determined from the input signal including the first elements such that applying the sampling procedure to the first elements results in the input signal. According to the type of the signal, a guiding set is determined including second elements disjoint from the first elements. A reconstruction set including third elements is generated so that the third elements minimize a sum of a first similarity measure of the third elements to the second elements and a second similarity measure of the third elements to the first elements. A transformed signal that minimizes a function on the reconstruction set is determined. A reconstructed signal is rendered so that a third similarity measure of the reconstructed signal to the transformed signal is smaller than a tolerance.
Abstract:
Videos of a scene are processed for view synthesis. The videos are acquired by corresponding cameras arranged so that a view of each camera overlaps with the view of at least one other camera. For each current block, motion or disparity vector is obtained from neighboring blocks. A depth block is based on a corresponding reference depth image and the motion or disparity vector. A prediction block is generated based on the depth block using backward warping. Then, predictive coding for the current block using the prediction block.