Point Cloud Data Transmission Using Layered Encoding
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Solution Overview
Problem
Existing methods for processing point cloud data face challenges in efficiency and complexity, particularly in terms of latency and encoding/decoding processes, which hinder effective transmission and rendering of high-quality point cloud content for applications like VR and self-driving services.
Innovation Solution
A method and device for encoding and transmitting point cloud data as a bitstream, utilizing techniques such as geometry-based and video-based point cloud compression coding, along with scalable attribute coding, to efficiently process and render point cloud content, reducing latency and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point cloud data is transmitted with high quality for VR and self-driving services, then service quality is improved, but data transmission latency increases
Solution Approach 1:
The patent segments point cloud data into multiple layers including base layer and enhancement layers, allowing progressive transmission where critical base information is sent first for low-latency rendering, followed by enhancement data for improved quality. This resolves the contradiction by enabling quality-adaptive transmission that prioritizes timing-critical components.
Solution Approach 2:
The patent performs preliminary encoding and prioritization of point cloud data before transmission, pre-processing data to identify and separate time-critical from non-critical information. This allows the system to prepare optimized data streams in advance, reducing actual transmission latency while maintaining service quality.
2Reliability
If detailed point cloud data is processed to maintain high quality, then rendering quality is improved, but encoding/decoding complexity increases
Solution Approach 1:
The patent divides point cloud data into spatial segments and attribute segments, processing different portions with different complexity levels. This segmentation allows the system to maintain high rendering quality for critical regions while using simplified processing for less important areas, thereby reducing overall encoding/decoding complexity.
Solution Approach 2:
The patent applies different processing qualities to different regions of the point cloud data based on their importance. High-quality encoding is applied to regions requiring detailed rendering, while lower-quality encoding is used for less critical regions, optimizing the balance between rendering quality and processing complexity.
3Reliability
If comprehensive point cloud data is transmitted to ensure service quality, then service reliability is improved, but transmission efficiency decreases
Solution Approach 1:
The patent extracts and transmits only the essential and critical point cloud data attributes and points required for service functionality, excluding redundant information. This extraction approach maintains service reliability by ensuring all necessary data is transmitted while improving efficiency by removing unnecessary data overhead.
Solution Approach 2:
The patent implements partial transmission of point cloud data by sending base layer information fully and enhancement layer information selectively based on bandwidth and quality requirements. This partial action approach ensures service reliability through complete base data transmission while improving efficiency through selective enhancement data transmission.
Data Source
AI summary
A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream including the point cloud data. A point cloud data reception device according to embodiments may comprise: a receiver which receives a bitstream including point cloud data; and a decoder which decodes the point cloud data.