Point Cloud Slice Headers for Low-Latency Bitstream 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 crucial for applications like VR, AR, and self-driving services.
Innovation Solution
A method and device for encoding and transmitting point cloud data through bitstreams, followed by decoding and rendering, utilizing geometry-based and video-based compression techniques to optimize data processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point cloud data is transmitted with high quality, then service quality is improved, but data transmission time and latency increase
Solution Approach 1:
The point cloud data is divided into multiple slices, where each slice contains a portion of the encoded point cloud data. This segmentation allows the receiver to reconstruct and display point cloud content from individual slices independently, enabling faster transmission and reduced latency while maintaining service quality. The slice structure facilitates parallel processing and selective decoding of critical data portions.
2Manufacturing precision
If point cloud data is processed with high detail, then manufacturing precision is improved, but processing complexity increases
Solution Approach 1:
The point cloud data is pre-encoded into slices with embedded reconstruction information before transmission. This preliminary encoding action includes organizing the data into a structured format with headers and payload sections that contain all necessary information for accurate reconstruction. By performing this preparation in advance, the receiver can efficiently decode and reconstruct high-precision point cloud data without requiring complex real-time processing.
3Loss of information
If complete point cloud data is transmitted, then information completeness is improved, but transmission data volume increases
Solution Approach 1:
The essential reconstruction information is extracted and placed in the slice header, while the actual point cloud data is organized in the payload section. This extraction allows the receiver to obtain complete point cloud information through selective decoding of slice headers and payload sections, reducing the effective data volume that needs to be processed while maintaining information completeness. The structured format enables efficient data transmission by separating critical metadata from bulk data.
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 method according to embodiments may comprise the steps of: receiving a bitstream including point cloud data; and decoding the point cloud data.


