3D Surface Modeling with Image-Guided Mesh Opacity Refinement
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Solution Overview
Problem
Creating three-dimensional digital models of complex-shaped objects is challenging due to difficulties in determining which triangles belong to the object's surface and which do not, leading to imperfect opacity determination and model flaws, often requiring lengthy human intervention.
Innovation Solution
A method that uses images from multiple viewpoints to determine opacity and texture parameters for triangles by iteratively aligning a draft model with these images, incorporating a gradient backpropagation method to converge towards an optimal configuration, reducing defects in the final model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a region growth algorithm is used to determine triangle opacity, then the mesh can be processed automatically, but the accuracy of opacity determination deteriorates for complex-shaped objects
Solution Approach 1:
The patent implements an iterative optimization process where the draft model is compared against multiple images, and the opacity and texture parameters are adjusted based on the consistency error. This feedback loop continues until convergence, allowing automatic processing to achieve high accuracy by continuously refining the opacity determination based on actual image data.
Solution Approach 2:
The patent changes the approach from binary opaque/transparent classification to continuous opacity parameter optimization. By treating opacity as a adjustable parameter that can be refined through gradient descent optimization rather than fixed by region growth algorithms, the system achieves both automation and high precision for complex geometries.
2Manufacturing precision
If multiple images from different viewpoints are used to determine opacity and texture, then the accuracy of the three-dimensional model improves, but the computing resources and processing time required increase
Solution Approach 1:
The patent replaces traditional mechanical region growth algorithms with a gradient-based optimization approach. By using gradient descent to minimize the difference between the draft model and actual images, the system efficiently handles multiple viewpoints without the computational burden of exhaustive region growth analysis, achieving high accuracy with reduced computing resources.
3Ease of operation
If region growth algorithm is used to determine triangle opacity, then processing can be performed without human intervention, but the number of defects in the final model increases
Solution Approach 1:
The patent implements a self-service optimization system where the draft model automatically refines its own opacity and texture parameters by comparing itself against the input images. The gradient descent optimization allows the system to self-correct defects without human intervention, maintaining both ease of operation and high model reliability through automatic iterative improvement.
Data Source
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AI summary
A method for digitally digitizing a three-dimensional surface, comprising the steps of: determining point coordinates on the three-dimensional surface to obtain a point cloud and capturing images of the three-dimensional surface, constructing a mesh of triangles on the point cloud by tetrahedrization, projecting the mesh onto the images and simultaneously determining an opacity parameter and a texture parameter of the triangles by coinciding at least a part of the images and the mesh in order to obtain a draft three-dimensional model, comparing the draft three-dimensional model to the images and verifying consistency between the draft three-dimensional model and the images, returning to the determination of the opacity and texture parameters of the triangles if the consistency is less than an expected consistency, extracting the surface from the draft model to form the three-dimensional model otherwise.