3D Point Cloud Attribute Coding With Layered Quantization Control
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Solution Overview
Problem
Existing methods for encoding three-dimensional data, such as point cloud data, face challenges in efficiently compressing and transmitting large data volumes while maintaining quality, particularly in applications like autonomous vehicles and robotics.
Innovation Solution
A method involving calculating coefficient values from attribute information, quantizing them into layers with specific quantization parameters, and generating a bitstream that includes reference and additional quantization parameters for improved encoding and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is compressed using traditional encoding methods, then data transmission efficiency is improved, but decoding accuracy and quality deteriorate
Solution Approach 1:
The patent applies parameter changes by introducing layer-specific quantization parameters (QP) that can be independently adjusted for different layers of the point cloud data hierarchy. This allows the encoder to optimize compression for each layer based on its importance, transmitting essential geometric information with higher precision while applying more aggressive compression to less critical attributes, thus resolving the contradiction between compression efficiency and decoding accuracy
Solution Approach 2:
The patent implements local quality by assigning different quantization parameters to different layers of the point cloud data structure. Critical layers (e.g., those containing essential geometric information) receive finer quantization with smaller QP values to maintain high decoding accuracy, while non-critical layers use coarser quantization with larger QP values to improve overall compression efficiency. This layered approach ensures that decoding accuracy is maintained where it matters most while achieving better overall transmission efficiency
2Productivity
If quantization parameters are optimized for each layer, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the point cloud data into multiple layers with different levels of importance or detail. Each layer is then processed with its own quantization parameter, allowing the encoder to optimize coding efficiency for each segment independently. This segmentation approach improves overall coding efficiency by applying appropriate compression levels to different data portions while keeping the complexity manageable through the structured layering approach
Solution Approach 2:
The patent implements dynamics by making quantization parameters adaptive and variable across different layers rather than using a single fixed parameter for all data. The encoder dynamically selects and applies different QP values based on the specific characteristics and importance of each layer, allowing for optimized coding efficiency while the systematic layer management keeps implementation complexity reasonable
3Device complexity
If a reference quantization parameter is used across layers, then device complexity is reduced, but adaptability to different data characteristics deteriorates
Solution Approach 1:
The patent applies parameter changes by introducing a reference quantization parameter that serves as a baseline, with additional layer-specific offset parameters that can be selectively applied. This hybrid approach maintains relatively low device complexity by using a single reference parameter for all layers while providing the adaptability to adjust individual layer parameters when needed, thus resolving the contradiction between complexity reduction and adaptability maintenance
Data Source
AI summary
A three-dimensional data encoding method includes: calculating coefficient values from pieces of attribute information of three-dimensional points included in point cloud data; quantizing the coefficient values individually to generate quantized values; and generating a bitstream including the quantized values. Each of the coefficient values belongs to any one of layers. In the quantizing, each of the coefficient values is quantized using a quantization parameter for a layer to which the coefficient value belongs among the layers, and the bitstream includes first information and pieces of second information, the first information indicating a reference quantization parameter, the pieces of second information being for calculating quantization parameters for the layers from the reference quantization parameter.