3D Textured Mesh Compression for Connectivity-Preserving Bitstreams
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Solution Overview
Problem
Existing video-based solutions for compressing 3D volumetric data, such as V3C, are inefficient in encoding connectivity information of 3D meshes, which cannot be effectively compressed using traditional video coding technologies.
Innovation Solution
A method for compressing 3D textured meshes by pre-processing to generate a base mesh and displacement field, involving decimation, subdivision, and wavelet transforms, followed by encoding with video codecs to produce a compressed bitstream, and decoding to reconstruct the mesh.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video coding technologies are used to compress 3D mesh data, then compression efficiency is improved, but connectivity information cannot be effectively compressed
Solution Approach 1:
The patent segments the 3D mesh data into two distinct components: connectivity information (topology) and geometry/attribute information. The connectivity data is encoded using dedicated mesh coding techniques that preserve topological relationships, while geometry and attributes are projected onto 2D planes and compressed using video coding technologies. This segmentation allows each component to be compressed with the most appropriate method, preventing loss of connectivity information while maintaining high compression efficiency.
2Loss of information
If 3D mesh data is compressed without preprocessing, then data integrity is maintained, but compression performance is poor
Solution Approach 1:
The patent applies preliminary actions to the 3D mesh data before compression: (1) Decimation to reduce mesh complexity while preserving essential features, (2) Subdivision to create a refined base mesh that captures fine geometric details, and (3) Wavelet transform to decompose the displacement field into frequency components. These preprocessing steps transform the original mesh into a form that is much more amenable to compression, achieving high compression performance while maintaining data integrity through reversible transformations.
3Measurement precision
If high resolution mesh data is compressed, then reconstruction quality is improved, but bitstream size increases
Solution Approach 1:
The patent employs parameter changes at multiple levels to achieve high reconstruction quality with compact bitstream size: (1) The wavelet transform decomposes displacement data into frequency bands, allowing selective quantization where high-frequency components (less visually important) are coarsely quantized and low-frequency components (visually important) are finely quantized, (2) The subdivision level can be adjusted to control the base mesh resolution, and (3) Video coding parameters can be tuned to achieve desired quality-bitrate tradeoffs. These parameter changes enable adaptive control of reconstruction quality independent of bitstream size.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient compression and reconstruction of 3D meshes with improved rate-distortion performance and scalability, enabling spatial, quality, and temporal adaptability.
Implementation Method 1
performing a wavelet transform on the updated displacement field d′(i) to generate a plurality of wavelet coefficients
Data Source
AI summary
A method of compressing a 3D textured mesh M(i), the 3D textured mesh being defined by connectivity C(i), geometry G(i), texture coordinates T(i), and texture connectivity CT(i), wherein the mesh is associated with one or more 2D image attribute maps A(i) describing attributes associated with the mesh surface, can include pre-processing 3D textured mesh M(i) and attribute maps A(i) to generate a base mesh m(i) and displacement field d(i); and processing 3D textured mesh M(i), attribute maps A(i), base mesh m(i), and the displacement field d(i) to generate a compressed bitstream b(i).