Point Cloud Data Transmission via Layered V-PCC Encoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in efficiently transmitting and receiving point cloud data due to high latency and encoding/decoding complexity, particularly in supporting services like virtual reality, augmented reality, mixed reality, and self-driving applications.
Innovation Solution
The development of a method and devices for efficiently transmitting and receiving point cloud data, which involves encoding the data, transmitting it, receiving it, and decoding it, while addressing latency and encoding/decoding complexity through innovative compression techniques such as video-based point cloud compression (V-PCC).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional point cloud transmission methods are used, then the system is simple, but latency is high and encoding/decoding complexity is excessive
Solution Approach 1:
The patent segments point cloud data into multiple layers (base layer and enhancement layers) with different quality levels. The base layer contains essential geometric information for basic reconstruction, while enhancement layers add detailed surface and color information. This segmentation enables progressive decoding and reduces latency by allowing receivers to process only necessary layers first.
Solution Approach 2:
The patent implements dynamic adaptation of encoding and decoding parameters based on network conditions and service requirements. The system can dynamically adjust the number of enhancement layers, bitrates, and resolution levels to balance between encoding/decoding complexity and latency requirements for different applications.
2Reliability
If high-quality point cloud data is transmitted, then service quality is improved, but transmission efficiency decreases
Solution Approach 1:
The patent applies different quality levels to different regions and layers of point cloud data. Important regions with detailed surface geometry receive higher quality encoding in enhancement layers, while less critical regions use lower quality encoding. This local quality differentiation maintains service quality for essential areas while improving overall transmission efficiency.
Solution Approach 2:
The patent changes encoding parameters such as bitrate, resolution, and compression level adaptively based on the specific requirements of different point cloud services. The system can adjust these parameters to optimize the balance between output quality and transmission efficiency for various applications like VR, AR, and autonomous driving.
3Adaptability or versatility
If comprehensive point cloud services are provided, then versatility is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal point cloud transmission system that can support multiple services (VR, AR, MR, autonomous driving) through a common framework. The base layer provides universal geometric data that works for all services, while enhancement layers can be selectively added based on specific service requirements, avoiding the need for separate complex systems for each application.
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 a bitstream comprising point cloud data; and decoding the point cloud data.