Point Cloud Data Transmission via Spatial Region Segmentation
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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 in providing optimized content to users in virtual reality, augmented reality, and autonomous driving applications.
Innovation Solution
A method and system for efficiently transmitting and receiving point cloud data by encoding it, encapsulating the encoded data into a bitstream, and transmitting it as a file, which includes geometry data, attribute data, or occupancy map data, with signaling data that includes spatial region information, identification information, and priority/dependency information, allowing for optimized rendering based on viewport information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point cloud data is transmitted with high throughput to ensure data quality, then the completeness and quality of point cloud content is improved, but the transmission time and latency increase
Solution Approach 1:
The point cloud data is divided into multiple spatial regions (tiles), allowing selective transmission of only the viewport-related regions. This segmentation enables the system to transmit a subset of the total data at high quality while reducing overall transmission time and latency.
Solution Approach 2:
The patent applies different quality levels to different spatial regions based on their importance to the current viewport. Viewport-related regions are transmitted with high quality to ensure visual fidelity, while non-viewport regions use lower quality or are omitted entirely, optimizing the trade-off between data quality and transmission time.
2Reliability
If all point cloud data is encoded and transmitted to ensure complete content delivery, then the completeness of point cloud content is improved, but the encoding and decoding complexity increases
Solution Approach 1:
The patent extracts and transmits only the essential viewport-related portions of the point cloud data, removing unnecessary non-viewport regions. This extraction approach maintains content completeness for the user's current view while significantly reducing encoding and decoding complexity by processing only relevant data subsets.
Solution Approach 2:
The system dynamically determines which spatial regions to encode and transmit based on real-time viewport information. This dynamic adaptation allows the encoding complexity to vary according to user viewing behavior, encoding only the necessary regions rather than always processing the entire point cloud dataset.
3Productivity
If viewport information is signaled in the bitstream to enable optimized rendering, then the rendering efficiency is improved, but the data transmission size increases
Solution Approach 1:
The patent signals viewport information selectively rather than providing complete viewport data for all possible views. By providing partial viewport signaling information corresponding to actual user viewing behavior, the system achieves rendering efficiency improvements while minimizing the additional bitstream overhead.
Data Source
AI summary
Disclosed herein is a transmitting method and a receiving method of point cloud data. The transmitting method may include encoding point cloud data, encapsulating a bitstream that includes the encoded point cloud data into a file, and transmitting the file, the point cloud data include at least geometry data, attribute data, or an occupancy map data, the bitstream is stored in multiple tracks of the file, the file further includes signaling data, and the signaling data include spatial region information of the point cloud data.