Point cloud compression and decompression method based on octree coding and voxel context
A context and decompression technology, applied in image coding, instrumentation, computing, etc., can solve problems such as unsatisfactory compression effect, insufficient compression of redundant information, inability to make full use of point cloud space context information and overall structural data compression, etc. Achieve optimal compression performance and good compression effect
Active Publication Date: 2021-08-20
BEIHANG UNIV
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[0005] In view of this, the present invention provides a point cloud compression and decompression method based on octree coding and voxel context, which uses an octree structure to structure sparse and disordered point clouds in three-dimensional space, Combined with the spatial context information to compress the octree structure code, and optimize the reconstructed point cloud coordinates through the spatial context, it effectively solves the problem that the existing point cloud data compression methods cannot fully utilize the spatial context information and overall structure of the point cloud for data compression. The redundant information cannot be fully compressed, resulting in unsatisfactory compression effects and other problems
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[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0029] See attached figure 1 with figure 2 , the embodiment of the present invention discloses a point cloud compression and decompression method based on octree coding and voxel context, the method comprising:
[0030] S1: Voxelize the original point cloud data, and establish a corresponding octree structure, and use node codes to represent the child nodes of each non-leaf node in the octree structure.
[0031] In this embodiment, firstly, the original poi...
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The invention discloses a point cloud compression and decompression method based on octree coding and voxel context, which is based on the advantages of voxel and octree methods, introduces local voxel context into a depth entropy model so as to better compress octree structure data, can be applied to static and dynamic point cloud compression, according to the method, a coordinate optimization scheme based on voxel context is used to generate more accurate leaf node coordinates at a decoder end, and better compression performance can be achieved in static and dynamic point cloud geometric compression.
Description
technical field [0001] The present invention relates to the technical field of point cloud data compression and decompression, and more specifically relates to a point cloud compression and decompression method based on octree coding and voxel context. Background technique [0002] At present, artificial intelligence has revolutionized the visual perception ability of robots. Machines based on these AI algorithms usually utilize many different sensors to perceive and interact with the world. In particular, due to their ability to accurately capture the 3D geometry of a scene, LiDAR has proven to be crucial in many types of machine scenarios (e.g., autonomous driving, indoor robots, robotic arms, and drones, etc.) And structured light scanners, these sensors are capable of producing massive amounts of data, with a single Velodyne HDL-64 LiDAR sensor producing more than 100,000 points per scan, while it can perform more than 84 billion scans per day. The huge volume of sensor...
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Login to View More IPC IPC(8): G06T9/40
CPCG06T9/40
Inventor 不公告发明人
Owner BEIHANG UNIV