Predictive geometry coding in G-PCC
    101.
    发明授权

    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.

    Position-dependent intra-inter prediction combination in video coding

    公开(公告)号:US11831875B2

    公开(公告)日:2023-11-28

    申请号:US17804329

    申请日:2022-05-27

    CPC classification number: H04N19/126 H04N19/176 H04N19/503 H04N19/593

    Abstract: A device for coding video data includes a processor configured to generate an inter-prediction block and an intra-prediction block for a current block of video data; for each sample of a prediction block to be generated: determine a first weight for the sample according to a position of the sample in the prediction block; determine a second weight for the sample according to the position of the sample in the prediction block; apply the first weight to a sample at the position in the inter-prediction block to generate a weighted inter-prediction sample; apply the second weight to a sample at the position in the intra-prediction block to generate a weighted intra-prediction sample; and calculate a value for the sample at the position in the prediction block using the weighted inter-prediction sample and the weighted intra-prediction sample; and code the current block using the prediction block.

    PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION

    公开(公告)号:US20230230290A1

    公开(公告)日:2023-07-20

    申请号:US18155480

    申请日:2023-01-17

    CPC classification number: G06T9/40

    Abstract: A method comprises: for each of a plurality of dimensions: identifying a reference position for the dimension, the reference position for the dimension being a position in a reference frame for the respective dimension, and the reference frame for the respective dimension and a reference frame for at least one other dimension in the plurality of dimensions being different reference frames in a plurality of reference frames; identifying an inter predictor for the respective dimension, wherein a predictor has a coordinate value in the respective dimension corresponding to a coordinate value in the respective dimension of the inter predictor for the respective dimension; and encoding or decoding the current point based on the predictor.

    MODEL-BASED PREDICTION FOR GEOMETRY POINT CLOUD COMPRESSION

    公开(公告)号:US20220215596A1

    公开(公告)日:2022-07-07

    申请号:US17562121

    申请日:2021-12-27

    Abstract: Techniques are disclosed for coding point cloud data using a scene model. An example device for coding point cloud data includes a memory configured to store the point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory. The one or more processors are configured to determine or obtain a scene model corresponding with a first frame of the point cloud data, wherein the scene model represents objects within a scene, the objects corresponding with at least a portion of the first frame of the point cloud data. The one or more processors are also configured to code a current frame of the point cloud data based on the scene model.

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