3D Model Texture Compression via Pattern-Instance Redundancy Removal
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Solution Overview
Problem
Existing methods for compressing 3D models with repetitive structures are inefficient in handling texture information, as they do not effectively utilize the redundancy between repetitive textures, leading to suboptimal compression efficiency.
Innovation Solution
The method organizes 3D models into patterns and instances, re-arranges texture coordinates based on pattern geometry, and employs texture coding modes to predictively encode instance textures from pattern textures, removing redundancy and reducing the size of texture images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional compression methods are used for texture information, then the compression process is simple, but the compression efficiency is low and bitstream size is large
Solution Approach 1:
The patent applies copying by identifying repetitive texture patterns in the 3D model and storing only one instance of each unique texture. Subsequent occurrences of the same texture are represented by references to the stored pattern, significantly reducing the bitstream size while maintaining visual fidelity. This is achieved through texture pattern matching and instantiation mechanisms that copy texture information efficiently.
Solution Approach 2:
The patent segments texture information into distinct pattern instances, separating unique texture data from repetitive occurrences. By dividing the texture representation into pattern definitions and pattern instantiations, the system can compress repetitive textures more effectively while preserving the ability to reconstruct the original texture information accurately.
2Loss of information
If texture information is compressed without considering repetitive structures, then the processing is faster, but the compressed file size is larger
Solution Approach 1:
The patent applies preliminary action by performing texture pattern identification and clustering during the compression phase. The system pre-processes texture information to identify repetitive patterns and organize them into pattern instances before final encoding. This preliminary organization enables more efficient compression without significantly increasing the complexity of the decoding process.
Solution Approach 2:
The patent changes parameters by transforming texture coordinate representations to align with identified pattern instances. By modifying how texture coordinates are encoded—referencing pattern IDs and instance parameters rather than storing complete texture data—the system achieves better compression ratios while managing algorithmic complexity through parameter optimization.
3Productivity
If pattern-instance representation is used for geometry, then geometric compression is improved, but texture coordinate handling becomes more complex
Solution Approach 1:
The patent applies universality by creating a unified pattern-instance representation framework that handles both geometry and texture information simultaneously. The same pattern-instance structure used for geometric compression is extended to texture coordinate management, allowing the system to process both types of data through a single integrated mechanism rather than separate independent systems.
Solution Approach 2:
The patent introduces an intermediary layer that mediates between the pattern-instance geometric representation and texture coordinate data. This intermediary manages the mapping between geometric patterns and their corresponding texture instances, simplifying the overall process by providing a structured interface that handles the complexity of coordinating geometry and texture transformations.
Data Source
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AI summary
A 3D model can be modeled using "pattern-instance?representation. To describe the vertices and triangles, properties of the instance, for example, texture, color, and normal, are adjusted to correspond to the order in the pattern. The texture of an instance is encoded depending on its similarity with the texture of a corresponding pattern. When instance texture is identical or almost identical to the pattern texture, the instance texture is not encoded and the pattern texture will be used to reconstruct the instance texture. When the instance texture is similar to the pattern texture, the instance texture is predictively encoded from the pattern texture, that is, the difference between the instance texture and pattern texture is encoded, and the instance texture is determined as a combination of the pattern texture and the difference.