ATTRIBUTE CODING FOR POINT CLOUD COMPRESSION

    公开(公告)号:US20240331205A1

    公开(公告)日:2024-10-03

    申请号:US18624683

    申请日:2024-04-02

    CPC classification number: G06T9/001 G06T9/40

    Abstract: An example device for coding point cloud data includes: a memory configured to store point cloud data; and one or more processors implemented in circuitry and configured to: decode encoded point cloud geometry data for a point cloud to reconstruct point cloud geometry data for the point cloud; downscale the point cloud geometry data to form downscaled point cloud geometry data; and code attribute data for the point cloud using the downscaled point cloud geometry. When encoding the attribute data, the processors may encode the point cloud geometry data using a deep learning-based geometry encoder. When decoding the attribute data, the processors may upscale the downscaled point cloud attribute data. The processors may code a value representing an amount of downscaling to apply to the decoded point cloud geometry data.

    PREDICTIVE GEOMETRY CODING OF POINT CLOUD
    5.
    发明公开

    公开(公告)号:US20240144543A1

    公开(公告)日:2024-05-02

    申请号:US18486541

    申请日:2023-10-13

    CPC classification number: G06T9/40

    Abstract: An example device includes memory configured to store the point cloud data and one or more processors configured to determine a first point of the point cloud data to be a first node of a first prediction tree branch. The one or more processors are configured to determine that a first azimuth difference between the first point and a second point of the point cloud data does not meet a first azimuth threshold, and based on that determination, determine the second point to be a second node of the first prediction tree branch. The one or more processors are configured to determine that a second azimuth difference between a third point of the point cloud data and a fourth point of the point cloud data meets the first azimuth threshold and based on that determination, determine the fourth point to be a first node of a second prediction tree branch.

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