Hierarchical point cloud compression

    公开(公告)号:US10911787B2

    公开(公告)日:2021-02-02

    申请号:US16508202

    申请日:2019-07-10

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. To compress the attribute information, multiple levels of detail are generated based on an ordering of the points according to a space filling curve and attribute values are predicted. The attribute values may be predicted simultaneously while points are being assigned to different levels of detail. A decoder follows a similar prediction process based on level of details. Also, attribute correction values may be determined to correct predicted attribute values and may be used by a decoder to decompress a point cloud compressed using level of detail attribute compression. In some embodiments, attribute correction values may take into account an influence factor of respective points in a given level of detail on attributes in other levels of detail.

    Point cloud compression
    32.
    发明授权

    公开(公告)号:US10909726B2

    公开(公告)日:2021-02-02

    申请号:US16380928

    申请日:2019-04-10

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud. In some embodiments, an encoder may be configured to further compress points omitted from the image based representation. Also, in some embodiments, a decoder may be configured to decode points compressed outside of an image based representation or in a separate image based representation.

    Hierarchical point cloud compression

    公开(公告)号:US10897269B2

    公开(公告)日:2021-01-19

    申请号:US16133674

    申请日:2018-09-17

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. Attribute values for at least one starting point are included in a compressed attribute information file and attribute correction values used to correct predicted attribute values are included in the compressed attribute information file. Attribute values are predicted based, at least in part, on attribute values of neighboring points and distances between a particular point for whom an attribute value is being predicted and the neighboring points. The predicted attribute values are compared to attribute values of a point cloud prior to compression to determine attribute correction values. A decoder follows a similar prediction process as an encoder and corrects predicted values using attribute correction values included in a compressed attribute information file.

    POINT CLOUD COMPRESSION USING A SPACE FILLING CURVE FOR LEVEL OF DETAIL GENERATION

    公开(公告)号:US20200217937A1

    公开(公告)日:2020-07-09

    申请号:US16736703

    申请日:2020-01-07

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information. Attribute values for at least one starting point are included in a compressed attribute information file and attribute correction values are included in the compressed attribute information file. An order for the points is determined based on a space filling curve, wherein an encoder and a decoder determine a same order for the points based on the space filling curve. Levels of detail are determined by sampling the ordered points according to different sampling parameters, and attribute values are predicted for the points in the levels of detail using the determined order. The encoder determines attribute correction values based on a comparison of the predicted values to an original value prior to compression. The decoder corrects the predicted attribute values based on received attribute correction values.

    POINT CLOUD COMPRESSION USING FIXED-POINT NUMBERS

    公开(公告)号:US20200111236A1

    公开(公告)日:2020-04-09

    申请号:US16592711

    申请日:2019-10-03

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information. Attribute values for at least one starting point are included in a compressed attribute information file and attribute correction values are included in the compressed attribute information file. Attribute values are predicted based, at least in part, on attribute values of neighboring points. The predicted attribute values are compared to attribute values of a point cloud prior to compression to determine attribute correction values. In order to improve computing efficiency and/or repeatability, fixed-point number representations are used when determining predicted attribute values and attribute correction values. A decoder follows a similar prediction process as an encoder and corrects predicted values using attribute correction values included in a compressed attribute information file using fixed-point number representations.

    Point cloud geometry compression
    38.
    发明授权

    公开(公告)号:US10462485B2

    公开(公告)日:2019-10-29

    申请号:US16121501

    申请日:2018-09-04

    Applicant: Apple Inc.

    Abstract: A system comprises an encoder configured to compress a point cloud comprising a plurality of points each point comprising spatial information for the point. The encoder is configured to sub-sample the points and determine subdivision locations for the subsampled points. Also, the encoder is configured to determine, for respective subdivision location, if a point is to be included, not included, or relocated relative to the subdivision location. The encoder encodes spatial information for the sub-sampled points and encodes subdivision location point inclusion/relocation information to generate a compressed point cloud. A decoder recreates an original or near replica of an original point cloud based on the spatial information and the subdivision location inclusion/relocation information included in the compressed point cloud.

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