Octree-Segmented Point Cloud Bitstreams for Low-Latency Decoding
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing large amounts of point cloud data due to latency and encoding/decoding complexity, which is necessary for providing high-quality services such as VR and self-driving applications.
Innovation Solution
A method and device for encoding and transmitting point cloud data through bitstreams, utilizing geometry-based and video-based compression techniques, and decoding the data efficiently using feedback information to optimize processing based on user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point cloud data is transmitted with high quality for VR and self-driving services, then service quality is improved, but latency and encoding/decoding complexity increase
Solution Approach 1:
The point cloud data is divided into multiple octrees, and each octree is further divided into multiple sub-octrees. This segmentation allows parallel processing of different sub-octrees, reducing overall encoding and decoding latency while maintaining high service quality for VR and self-driving applications.
Solution Approach 2:
The patent performs preliminary segmentation of point cloud data into octrees and sub-octrees before transmission. This preliminary organization enables the receiving device to efficiently decode and process only the necessary portions of data, reducing latency in critical applications like self-driving and VR.
2Reliability
If point cloud data is transmitted with high quality for VR and self-driving services, then service quality is improved, but encoding/decoding complexity increases
Solution Approach 1:
By dividing the point cloud into multiple octrees and sub-octrees, the encoding and decoding processes can be distributed and parallelized. This segmentation reduces the computational complexity of processing the entire point cloud at once while maintaining high service quality.
Solution Approach 2:
The patent enables selective decoding of only the necessary sub-octrees based on application requirements. For self-driving and VR services, only relevant portions of the point cloud data need to be decoded in real-time, reducing overall decoding complexity while maintaining service quality.
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 including the point cloud data. A point cloud data reception device according to embodiments may comprise: a reception unit for receiving a bitstream including point cloud data; and a decoder for decoding the point cloud data.