3D Point Cloud Encoding Using Adaptive Occupancy Patterns
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Solution Overview
Problem
Current methods for encoding and decoding three-dimensional data lack efficiency, particularly in representing and transmitting large volumes of point cloud data.
Innovation Solution
A method and device for improving coding efficiency by selecting an occupancy pattern of neighboring nodes based on a flag, allowing for efficient encoding and decoding of three-dimensional data without dividing nodes into child nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is encoded using conventional methods, then data compression is achieved, but coding efficiency is insufficient for large volumes of three-dimensional data
Solution Approach 1:
The patent segments the N-ary tree structure into parent nodes and child nodes, creating a hierarchical representation where occupancy patterns of neighboring nodes are determined. This segmentation allows efficient encoding by processing nodes in a structured manner, determining whether to encode position information based on occupancy patterns rather than processing all points uniformly, thereby improving coding efficiency for large point cloud datasets
Solution Approach 2:
The patent introduces dynamic selection of occupancy patterns based on a first flag, allowing the encoding process to adapt between different occupancy pattern types (first occupancy pattern including parent node, second occupancy pattern excluding parent node). This dynamic adaptation enables the system to optimize coding efficiency by selecting the appropriate occupancy pattern for different data characteristics and compression requirements
2Speed
If three-dimensional data is transmitted without efficient encoding, then data transmission bandwidth is high, but data processing speed is slow
Solution Approach 1:
The patent changes the encoding parameters by determining usability of first encoding based on occupancy patterns of neighboring nodes. By adjusting the encoding approach according to the occupancy pattern (whether parent node is included or excluded), the system optimizes the balance between compression ratio and processing speed, enabling faster data processing while maintaining efficient bandwidth utilization
Data Source
AI summary
A three-dimensional data encoding method includes: (i) when a first flag indicates a first value, creating a first occupancy pattern indicating occupancy states of second neighboring nodes including a first neighboring node having a parent node different from a parent node of a current node included in an N-ary tree structure of three-dimensional points included in three-dimensional data, and determining whether first encoding is usable based on the first occupancy pattern, the first encoding being for encoding pieces of position information of three-dimensional points included in the current node without dividing the current node into child nodes; (ii) when the first flag indicates a second value, creating a second occupancy pattern indicating occupancy states of third neighboring nodes excluding the first neighboring node, and determining whether the first encoding is usable based on the second occupancy pattern; and (iii) generating a bitstream including the first flag.