Point Cloud Bitstream Layering for Low-Latency Transmission
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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 layers including base layer and enhancement layers. The base layer contains essential data for basic service quality, while enhancement layers provide additional quality improvements. This segmentation allows progressive transmission where core services are delivered first with lower latency, and quality enhancements are added subsequently.
Solution Approach 2:
The patent employs variable bitrate encoding where different portions of point cloud data are encoded at different bitrates based on their importance. Critical geometric data uses higher compression ratios while attribute data uses lower compression ratios, optimizing the balance between transmission time and service quality.
2Productivity
If point cloud data is compressed heavily, then transmission efficiency is improved, but decoding complexity increases
Solution Approach 1:
The compression process is segmented into multiple passes: a first pass generates a base layer with simpler compression for faster decoding, while a second pass adds enhancement data with more complex compression. The decoder can operate at different complexity levels by processing only the necessary layers, reducing the effective decoding complexity for real-time applications.
Solution Approach 2:
The system implements progressive decoding where the decoder processes data in stages. For time-sensitive applications, only the base layer is decoded providing sufficient quality with lower complexity. Full quality decoding of all layers is optional and can be performed when computational resources are available and time permits.
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 comprising the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of: receiving a bitstream comprising point cloud data; and decoding the point cloud data.