The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 14, 2021

Filed:

Feb. 12, 2018
Applicant:

Peking University Shenzhen Graduate School, Guangdong, CN;

Inventors:

Ge Li, Guangdong, CN;

Yiting Shao, Guangdong, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/593 (2014.01); H04N 19/136 (2014.01); H04N 19/156 (2014.01); H04N 19/159 (2014.01); H04N 19/176 (2014.01); H04N 19/186 (2014.01); H04N 19/61 (2014.01); H04N 19/625 (2014.01); H04N 19/91 (2014.01); H04N 19/96 (2014.01);
U.S. Cl.
CPC ...
H04N 19/593 (2014.11); H04N 19/136 (2014.11); H04N 19/156 (2014.11); H04N 19/159 (2014.11); H04N 19/176 (2014.11); H04N 19/186 (2014.11); H04N 19/61 (2014.11); H04N 19/625 (2014.11); H04N 19/91 (2014.11); H04N 19/96 (2014.11);
Abstract

An intra-frame prediction-based point cloud attribute compression method. A new block structure-based intra-frame prediction scheme is provided for point cloud attribute information, where four prediction modes are provided to reduce information redundancy among different coding blocks as much as possible and improve point cloud attribute compression performance. The method comprises: performing point cloud attribute color space conversion; dividing a point cloud by using a K-dimensional (KD) tree to obtain coding blocks; performing block structure-based intra-frame prediction; performing intra-frame prediction mode division; performing conversion, uniform quantization, and entropy coding. The method relates to performing coding block division on a point cloud by using a KD tree, numbering coding blocks in a breadth-first traversal order, processing the coding blocks one by one in the numbering order by using a point cloud intra-frame prediction scheme having four prediction modes, selecting an optical prediction mode by means of mode decision, and performing conversion, quantization, and entropy coding on a predicted residual, so as to achieve optimal performance of point cloud attribute compression.


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