V-Mesh Compression for Low-Latency Point Cloud Transmission
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Solution Overview
Problem
Generating and transmitting point cloud data is challenging due to its large volume and the high throughput required, as well as issues with latency and encoding/decoding complexity.
Innovation Solution
A method for encoding and transmitting mesh data using Video-based Dynamic Mesh (V-Mesh) compression, which includes pre-processing, encoding, and decoding processes to efficiently transmit and receive point cloud data, utilizing techniques like intra-frame and inter-frame encoding, and applying video codecs for efficient data transmission and reception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point cloud data is transmitted with high quality, then data fidelity is improved, but transmission bandwidth requirement increases
Solution Approach 1:
The patent segments the point cloud data into multiple octrees based on spatial distribution and complexity. Each octree can be processed and transmitted independently, allowing selective transmission of only the necessary detail levels. This segmentation enables quality preservation for important regions while reducing overall bandwidth consumption.
Solution Approach 2:
The patent applies different compression and transmission strategies to different regions of the point cloud data. Areas with higher detail requirements maintain higher quality while less important regions use lower quality transmission. This local quality approach ensures critical data fidelity while optimizing overall bandwidth efficiency.
2Loss of time
If real-time transmission is achieved, then latency is reduced, but encoding complexity increases
Solution Approach 1:
The patent performs preliminary processing by building octree structures and pre-computing spatial hierarchies before actual transmission. This preparation allows the transmission system to operate more efficiently during real-time operation, reducing latency while managing encoding complexity through advance computation of data organization structures.
Solution Approach 2:
The patent implements dynamic adaptation of the octree decomposition level and transmission parameters based on real-time conditions. The system can adjust the balance between compression and detail preservation dynamically, enabling real-time transmission while managing encoding complexity through adaptive rather than fixed processing.
3Quantity of substance
If data compression is applied, then transmission bandwidth is reduced, but decoding complexity increases
Solution Approach 1:
The patent segments the compression process into manageable octree levels that can be decoded systematically. Each octree level maintains a structured format that simplifies the decoding process compared to traditional point cloud compression. The hierarchical segmentation allows incremental decoding while maintaining bandwidth efficiency.
Solution Approach 2:
The patent designs the compression scheme to maintain relatively uniform complexity across different decoding operations. By using consistent octree-based structuring throughout the data, the decoding process encounters similar complexity levels rather than varying difficulty, making the overall decoding more manageable while achieving good compression ratios.
Data Source
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AI summary
A mesh data transmission method according to embodiments may comprise the steps of: encoding mesh data; and transmitting a bitstream including the mesh data. A mesh data reception method according to embodiments may comprise the steps of: receiving a bitstream including mesh data; and decoding the mesh data.