Point Cloud Data Transmission Segmentation
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Solution Overview
Problem
Existing methods for transmitting and receiving point cloud data face challenges in efficiency due to high latency and encoding/decoding complexity, particularly when dealing with large datasets required for virtual reality, augmented reality, and self-driving applications.
Innovation Solution
A method involving encoding point cloud data, encapsulating it, and transmitting it efficiently, along with a corresponding decoding and rendering process at the reception end, utilizing techniques like Video-based Point Cloud Compression (V-PCC) to optimize data transmission and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is transmitted using existing methods, then the data can be delivered, but the transmission efficiency is low due to high latency and encoding/decoding complexity
Solution Approach 1:
The patent segments point cloud data into multiple packets for transmission, where each packet contains a portion of the point cloud data along with necessary header information. This segmentation allows for parallel processing and reduces the computational burden on individual encoding/decoding operations, thereby improving transmission efficiency while managing complexity.
Solution Approach 2:
The patent performs preliminary encoding and packetization of point cloud data before transmission, organizing the data into a structured format with headers containing metadata about each packet. This preliminary action reduces the complexity of real-time decoding operations at the receiving end, improving overall transmission efficiency.
2Loss of time
If point cloud data is transmitted using existing methods, then the data can be delivered, but the latency is high
Solution Approach 1:
The patent implements periodic transmission of point cloud data packets with structured headers, allowing the receiver to process packets in a systematic manner. This periodic structure enables optimized buffering and processing strategies that reduce latency while maintaining transmission efficiency.
Solution Approach 2:
The patent introduces structured packet headers as intermediaries that contain metadata about the point cloud data segments. These headers enable the receiving system to prepare for efficient decoding by anticipating data characteristics, thereby reducing processing latency without compromising transmission efficiency.
3Quantity of substance
If large point cloud datasets are processed, then comprehensive data is available, but the encoding/decoding complexity increases
Solution Approach 1:
The patent divides large point cloud datasets into multiple smaller packets, each with its own header containing relevant metadata. This segmentation reduces the complexity of encoding and decoding operations by processing smaller, manageable units in parallel, while still maintaining the completeness of the overall dataset.
Solution Approach 2:
The patent changes the parameter organization by introducing structured packet headers that contain metadata about data characteristics. This parameter reorganization enables more efficient processing algorithms that can handle large datasets with reduced complexity by leveraging the structured information in the headers.
Data Source
AI summary
Disclosed herein is a point cloud data transmission method. The transmission method may include encoding point cloud data, and transmitting point cloud data. Disclosed herein is a point cloud data reception device. Disclosed herein is a point cloud data reception method. The reception method may include receiving point cloud data, decoding the point cloud data, and rendering the point cloud data.