Point Cloud Transmission with Octree and Hybrid Compression
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing large amounts of point cloud data required for applications like virtual reality, augmented reality, and self-driving services due to high latency and encoding/decoding complexity.
Innovation Solution
A method and device for processing point cloud data using geometry-based and video-based compression techniques, including geometry-based point cloud compression (G-PCC) and video-based point cloud compression (V-PCC), along with encoding and decoding processes that utilize octree geometry coding, predictive tree geometry coding, and entropy encoding to reduce complexity and improve efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If geometry-based point cloud compression (G-PCC) is used, then encoding precision is improved, but encoding complexity increases
Solution Approach 1:
The point cloud data is divided into multiple blocks or regions, and each block is processed independently using octree-based segmentation. This allows the encoding process to handle smaller, manageable segments rather than the entire point cloud at once, reducing overall encoding complexity while maintaining precision through systematic processing of each segment.
Solution Approach 2:
The patent transforms the three-dimensional point cloud data into a hierarchical octree structure, adding a structural dimension to the data representation. This octree organization enables more efficient encoding by exploiting spatial relationships and redundancies across different levels of the tree, thereby improving precision without proportionally increasing complexity.
2Speed
If video-based point cloud compression (V-PCC) is used, then processing speed is improved, but compression efficiency deteriorates
Solution Approach 1:
The patent merges the advantages of both G-PCC and V-PCC approaches by combining geometry-based octree encoding with video-based predictive coding techniques. This hybrid method maintains the speed benefits of V-PCC while preserving the compression efficiency of G-PCC through integrated processing of temporal and spatial redundancies.
Solution Approach 2:
The encoding scheme uses a composite approach that combines multiple coding techniques (octree-based geometry coding, predictive coding, and entropy coding) into a unified framework. This composite method achieves both high processing speed and good compression efficiency by leveraging the strengths of each individual technique in appropriate contexts.
3Manufacturing precision
If large amounts of point data are processed, then representation quality is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary organization of point cloud data into octree structures and identifies spatial redundancies before the main encoding process. This preliminary action includes pre-processing steps such as voxelization and hierarchical organization, which reduce the complexity of subsequent encoding operations and enable faster processing of large datasets while maintaining high representation quality.
Solution Approach 2:
The patent replaces traditional mechanical processing methods with algorithmic approaches based on octree decomposition and entropy coding. This substitution enables efficient handling of large point clouds by using computational algorithms that exploit data structures and statistical properties, significantly reducing processing time compared to brute-force methods while preserving representation quality.
4Productivity
If octree geometry coding is used, then spatial efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent implements nested octree structures where smaller octrees are embedded within larger ones, creating a hierarchical organization of point cloud data. This nesting approach improves spatial efficiency by systematically dividing space at multiple levels, while the self-similar nature of nested octrees allows for reusable encoding templates and algorithms, thereby reducing overall computational complexity despite the increased structural detail.
Data Source
AI summary
A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream containing the point cloud data. In addition, a point cloud data transmission device according to embodiments may comprise: an encoder for encoding point cloud data; and a transmitter for transmitting a bitstream containing the point cloud data.