Point Cloud Transmission Using Layered 2D Video Compression
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Solution Overview
Problem
The challenge lies in efficiently transmitting and receiving large volumes of point cloud data while addressing latency and encoding/decoding complexity, which is crucial for providing high-quality services such as virtual reality, augmented reality, and self-driving applications.
Innovation Solution
A method involving encoding point cloud data, encapsulating it, and transmitting it through a system comprising a point cloud video acquirer, encoder, encapsulation module, and transmitter, followed by decoding and rendering at the reception end, utilizing both geometry-based and video-based compression schemes to optimize data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point cloud data is transmitted with high quality for VR/AR/self-driving services, then service quality is improved, but data volume and transmission bandwidth requirements increase
Solution Approach 1:
The point cloud data is segmented into multiple layers including base layer and enhancement layers, allowing progressive transmission where essential data is sent first and additional detail data is sent subsequently, reducing initial bandwidth requirements while maintaining quality
Solution Approach 2:
The system changes data representation parameters by converting 3D point cloud data into 2D video sequences through projection, enabling the use of efficient video compression standards (H.264, H.265, AV1) that significantly reduce data volume while preserving visual quality
2Loss of time
If point cloud data is transmitted in real-time for low-latency applications, then response time is improved, but encoding and decoding complexity increases
Solution Approach 1:
The patent replaces complex 3D geometric processing with 2D video coding mechanisms, substituting point cloud compression algorithms with mature video compression standards, thereby reducing computational complexity while enabling real-time processing
Solution Approach 2:
The system performs preliminary projection of 3D point clouds onto 2D planes before compression, pre-processing the data into a format that can be efficiently encoded using standard video codecs, reducing real-time encoding complexity
Data Source
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AI summary
Disclosed herein are a point cloud data transmission method including encoding point cloud data, and transmitting point cloud data, and a point cloud data reception method including receiving point cloud data, decoding the point cloud data, and rendering the point cloud data.