Clipping laser indices in predictive geometry coding for point cloud compression

    公开(公告)号:US12033360B2

    公开(公告)日:2024-07-09

    申请号:US17491114

    申请日:2021-09-30

    CPC classification number: G06T9/001 G01S17/89

    Abstract: A method of encoding a point cloud includes determining, by one or more processors, a quantity of lasers used to capture light detection and ranging (LIDAR) data that represents the point cloud; and encoding, by the one or more processors, a laser index for a current node of the point cloud, wherein encoding the laser index comprises: obtaining a predicted laser index value of the current node; determining a residual laser index value for the current node, wherein determining the residual laser index value comprises constraining a sum of the residual laser index value and the predicted laser index value to be less than or equal to the determined quantity of lasers minus one; and encoding, in a bitstream, one or more syntax elements that represent the residual laser index value.

    Machine learning based flow determination for video coding

    公开(公告)号:US12003734B2

    公开(公告)日:2024-06-04

    申请号:US17676510

    申请日:2022-02-21

    CPC classification number: H04N19/139 H04N19/172 H04N19/186 H04N23/632

    Abstract: Systems and techniques are described herein for processing video data. In some aspects, a method can include obtain, by a machine learning system, input video data. The input video data includes one or more luminance components for a current frame. The method can include determining, by the machine learning system, motion information for the luminance component(s) of the current frame and motion information for one or more chrominance components of the current frame using the luminance component(s) for the current frame. In some cases, the method can include determining the motion information for the luminance component(s) based on the luma component(s) of the current frame and at least one reconstructed luma component of a previous frame. In some cases, the method can further include determining the motion information for the chrominance component(s) of the current frame using the motion information determined for the luminance component(s) of the current frame.

    Gradient-based prediction refinement for video coding

    公开(公告)号:US11962796B2

    公开(公告)日:2024-04-16

    申请号:US16836013

    申请日:2020-03-31

    CPC classification number: H04N19/513

    Abstract: This disclosure describes gradient-based prediction refinement. A video coder (e.g., video encoder or video decoder) determines one or more prediction blocks for inter-predicting a current block (e.g., based on one or more motion vectors for the current block). In gradient-based prediction refinement, the video coder modifies one or more samples of the prediction block based on various factors such as displacement in a horizontal direction, the horizontal gradient, a displacement in the vertical direction, and a vertical gradient. This disclosure provides for gradient-based prediction refinement where a precision level of the displacement (e.g., at least one of the horizontal or vertical displacement) is unified (e.g., the same) for different prediction modes.

    DECODER-SIDE CONTROL POINT MOTION VECTOR REFINEMENT FOR AFFINE INTER-PREDICTION IN VIDEO CODING

    公开(公告)号:US20240121399A1

    公开(公告)日:2024-04-11

    申请号:US18476931

    申请日:2023-09-28

    CPC classification number: H04N19/139 H04N19/176 H04N19/517

    Abstract: An example device for decoding video data includes a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry, the processing system being configured to: refine a first control point motion vector (CPMV) of a current block of the video data using a first decoder-side motion vector refinement (DMVR) process to form a first refined CPMV for the current block; refine a second CPMV of the current block of video data using a second DMVR process, independently of the first DMVR process, to form a second refined CPMV for the current block; form a prediction block for the current block using the first refined CPMV and the second refined CPMV; and decode the current block using the prediction block. In some examples, the CPMVs may each be decoded using a respective merge index and a respective motion vector difference (MVD).

    INTRA PREDICTION FUSION WITH REDUCED COMPLEXITY IN VIDEO CODING

    公开(公告)号:US20240098257A1

    公开(公告)日:2024-03-21

    申请号:US18461255

    申请日:2023-09-05

    CPC classification number: H04N19/11 H04N19/176 H04N19/593

    Abstract: A video decoder may be configured to determine that a block of video data is encoded using an intra prediction process that utilizes multiple intra prediction predictors; determine a set of reference lines for the intra prediction process; determine a first set of intra prediction predictors based on the set of reference lines; determine a second set of intra prediction predictors based on the set of reference lines; generate a fusion of predictors from the first set of intra prediction predictors and the second set of intra prediction predictors; and decode the block of video data using the fusion of predictors.

    Predictive geometry coding in G-PCC

    公开(公告)号:US11935270B2

    公开(公告)日:2024-03-19

    申请号:US17449013

    申请日:2021-09-27

    CPC classification number: G06T9/001 G01S7/4808 G01S13/42 G06T9/40 G01S7/4802

    Abstract: An example method of decoding a point cloud includes selecting, from a plurality of predefined prediction modes, a prediction mode for performing predictive geometry coding of a position of a current node of the point cloud, wherein the plurality of prediction modes includes at least: a zero prediction mode, and a delta prediction mode; responsive to selecting the zero prediction mode: determining a radius, an azimuth, and a laser index of a parent node of the current node; inferring an azimuth and a laser index of a predicted position of the current node as the azimuth and the laser index of the parent node; inferring a radius of the predicted position to be a minimum radius value, wherein the minimum radius value is different than the radius of the parent node; and determining, based on the predicted position of the current node, the position of the current node.

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