Point Cloud Data Transmission Using V-PCC Patch Encoding
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Solution Overview
Problem
Existing methods for transmitting and receiving point cloud data face challenges in efficiency, latency, and encoding/decoding complexity, particularly due to the large volume of data and the need for high throughput in applications like virtual reality, augmented reality, and self-driving services.
Innovation Solution
A method and system for encoding and decoding point cloud data using video-based point cloud compression (V-PCC) techniques, which involve dividing point clouds into patches, generating occupancy maps, and encoding geometry and texture images, allowing for efficient transmission and rendering of point cloud content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is transmitted without compression, then data quality is maintained, but transmission throughput is insufficient and latency increases
Solution Approach 1:
The point cloud data is divided into multiple patches based on spatial segmentation. Each patch is processed and transmitted independently, allowing for efficient compression while maintaining overall data quality. The segmentation enables parallel processing and reduces the data volume for transmission without losing essential information.
Solution Approach 2:
The patent applies video-based point cloud compression (V-PCC) techniques that transform point cloud data into a format similar to conventional video data. This parameter transformation enables the use of成熟 video coding standards and tools for compression, significantly improving transmission efficiency while maintaining quality through controlled quality parameters.
2Quantity of substance
If traditional compression methods are used, then data size is reduced, but encoding/decoding complexity increases
Solution Approach 1:
The patent introduces an intermediary representation layer that converts point cloud data into a video-like format using V-PCC techniques. This intermediary format serves as a bridge between the original point cloud data and the compression process, enabling the use of existing video coding infrastructure to reduce complexity while achieving effective compression.
Solution Approach 2:
The patent leverages the universality of video coding standards and tools for point cloud compression. By transforming point cloud data into a video-like representation, the system can reuse成熟 video encoders and decoders, reducing the need for specialized complex compression algorithms and hardware.
3Manufacturing precision
If high-resolution point cloud data is transmitted, then service quality is improved, but transmission time and latency increase
Solution Approach 1:
The point cloud data is segmented into multiple patches that can be transmitted in parallel or at different priorities. This segmentation allows the system to transmit essential information faster while maintaining overall high-resolution quality, reducing latency for critical data without sacrificing service quality.
Solution Approach 2:
The V-PCC transformation enables flexible quality parameter adjustment during compression. The system can optimize quality parameters to balance transmission speed and service quality, allowing high-resolution data to be transmitted more efficiently by leveraging video coding optimizations.
Data Source
AI summary
A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of: receiving point cloud data; decoding the point cloud data; and rendering the point cloud data.