3D Texture Map Segmentation for Faster Model Customization
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Solution Overview
Problem
Existing 3D modeling software limits the ability to efficiently select and apply textures to multiple portions of a 3D model, requiring manual manipulation and leading to time-consuming and error-prone processes, especially when dealing with large numbers of different surfaces.
Innovation Solution
A system that maps a selected point on a 3D model to texture space and uses a segmentation algorithm, such as the 'Segment Anything Model', to identify and segment related portions of the texture map, allowing for automatic selection and modification of textures across the model without manual manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual manipulation of the 3D object is used to select and change textures, then the customization can be performed, but the process becomes tedious and time-consuming
Solution Approach 1:
The patent replaces manual mechanical manipulation of the 3D object with an automated image processing system. Users simply provide a 2D reference image, and the system automatically performs texture mapping, segmentation, and application to the 3D model, eliminating tedious manual operations and significantly reducing customization time
Solution Approach 2:
The system enables the 3D model to serve itself by automatically identifying and applying textures based on the provided reference image. The automated segmentation and texture mapping processes allow the model to customize itself without requiring manual intervention, improving ease of operation and reducing time loss
2Productivity
If automated texture mapping is implemented, then productivity is improved, but precision in selecting specific texture portions may be reduced
Solution Approach 1:
The patent applies segmentation to divide the texture map into distinct portions based on the reference image. This allows the automated system to accurately identify and select specific texture regions corresponding to different parts of the 3D model, maintaining precision while enabling high-speed automated processing of the entire model
Solution Approach 2:
The system transitions from 3D manual manipulation to 2D image-based automation. By working in the 2D domain of reference images and texture maps, the system achieves both automated efficiency and precise selection through image processing algorithms, resolving the contradiction between productivity and precision
Data Source
AI summary
A computer-implemented method is disclosed. The method includes: receiving an indication of a first point on a three-dimensional (3D) model; determining a second point in a texture map of the 3D model that corresponds to the first point; performing segmentation of the texture map for identifying portions of the texture map that are related to the second point; and outputting a 3D representation of the identified related portions of the texture map.


