Segment-Based Mesh Compression for High-Bitdepth Attribute Coding
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Solution Overview
Problem
Existing 3D media processing technologies face challenges in efficiently compressing and decompressing complex 3D models like meshes and point clouds, which require significant data resources for storage and transmission, leading to inefficiencies in immersive experiences.
Innovation Solution
The use of segment-based compression methods, including V-PCC and G-PCC codecs, that convert 3D point clouds into image-based representations, utilizing video coding techniques to encode geometry, texture, and occupancy maps, and employing patch generation and packing to minimize data volume while maintaining quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If segment-based compression methods are used to reduce data volume, then compression efficiency is improved, but complexity of the coding process increases
Solution Approach 1:
The mesh surface is divided into multiple spatial segments, and attribute values are encoded separately for each segment. This segmentation allows the system to handle complex 3D models by breaking them into manageable parts, achieving better compression ratios while maintaining manageable processing complexity through localized encoding operations.
Solution Approach 2:
The patent applies different bitdepths to different segments based on their specific attribute value ranges. By dynamically adjusting the precision parameter (bitdepth) for each segment according to its characteristics, the system optimizes compression efficiency without uniformly increasing complexity across the entire model.
2Loss of substance
If different bitdepths are used for different segments, then compression efficiency is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
Each spatial segment is assigned a specific bitdepth according to its local attribute value characteristics. This local quality approach allows the system to use higher precision only where needed while using lower precision elsewhere, optimizing overall compression while making bitdepth management more tractable through localized decision-making.
Solution Approach 2:
The system performs preliminary analysis of attribute value ranges for each segment before encoding, determining the appropriate bitdepth in advance. This preliminary action simplifies the actual encoding process by pre-establishing the precision requirements, reducing the complexity of real-time bitdepth management during compression.
Data Source
AI summary
Aspects of the disclosure provide methods and apparatuses for mesh coding (e.g., compression and decompression). In some examples, an apparatus for mesh coding includes processing circuitry. The processing circuitry decodes, using a decoder supporting a first bitdepth, a plurality of segmental attribute values having the first bitdepth from a bitstream carrying a mesh that represents a surface of an object. The plurality of segmental attribute values is associated with attribute values of the mesh, the attribute values of the mesh have a second bitdepth that is higher than the first bitdepth. The processing circuitry determines the attribute values of the mesh having the second bitdepth according to the plurality of segmental attribute values having the first bitdepth.