Adaptive Geometry Mode Selection in Point Cloud Octree Decoding
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Solution Overview
Problem
Existing point cloud coding and decoding methods based on octrees are inefficient for point cloud data with special geometry modes.
Innovation Solution
A method and apparatus for determining the geometry mode of a node by a decoder or coder using geometry information of reference, child, decoded child, or to-be-decoded child nodes, optimizing the coding and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If octree-based coding is used for point cloud data, then general point cloud data can be coded, but coding and decoding efficiency is low for point cloud data with special geometry modes
Solution Approach 1:
The patent applies dynamics by making the geometry mode determination adaptive rather than fixed. The decoder dynamically determines geometry modes based on geometric relationships between nodes in the octree structure, allowing the coding system to adapt to different geometry types (isolated points, planar surfaces, volumetric regions) without requiring separate coding paths for each mode.
Solution Approach 2:
The patent changes the parameter of geometry mode from a predetermined fixed value to a dynamically determined value based on spatial relationships. By calculating geometric relationships (such as whether child nodes are occupied based on parent node position and occupancy), the system optimizes coding efficiency for different geometry configurations without increasing overall system complexity.
2Stability of the object's composition
If octree partition mode is used to evenly divide bounding box, then point cloud data can be structured, but efficiency is low for special geometry modes
Solution Approach 1:
The patent applies local quality by allowing different geometry modes to be applied to different regions of the octree structure. Instead of using a single coding approach for the entire point cloud, the system determines geometry modes locally for each node based on its spatial relationships with neighboring nodes, optimizing coding efficiency for each local region while maintaining the overall octree structure.
3Device complexity
If geometry mode is not determined by decoder, then coding process is simple, but decoding efficiency is low
Solution Approach 1:
The patent applies self-service by enabling the decoder to autonomously determine geometry modes using only the coded information already present in the bitstream. The decoder calculates geometric relationships between nodes (such as determining whether child nodes are occupied based on parent node position and occupancy patterns) without requiring additional side information or complex coordination with the encoder, thereby improving decoding efficiency while maintaining system simplicity.
Data Source
AI summary
Some aspects of the disclosure provide a method of point cloud decoding by a decoder. In some examples, a bitstream of coded information of a point cloud is received. According to the coded information, respective geometry information of a plurality of first nodes in the point cloud are obtained. A geometry mode of a current node is determined according to the respective geometry information of the plurality of first nodes. The current node is a current to-be-decoded node in the point cloud. The plurality of first nodes include at least one of: a reference node of the current node, a child node of the reference node, a decoded child node of the current node, and/or a to-be-decoded child node of the current node. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.