3D Reconstruction Using Lexicographic Triangle Ordering

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Solution Overview

Problem

Existing 3D reconstruction methods are inefficient for scenes with corner structures, sensitive to noise and outliers, and require manual tuning of parameters, making them non-generic and not robust enough for diverse real-world scenarios.

Innovation Solution

A computer-implemented method for 3D reconstruction that determines a closed triangulated surface by penalizing high-ranked candidate surfaces based on a lexicographic order, which orders triangles by size and penalizes large triangles to accurately represent the skin of a structure without requiring smoothness hypotheses, thus handling non-regular structures and reducing the need for manual parameter tuning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If smoothness hypothesis methods are used for 3D reconstruction, then the reconstruction process is simplified, but the method fails for corner structures and non-regular scenes

Engineering Contradiction:
Improvesimplicity of reconstruction processVSAvoidapplicability to corner structures
Core Design Contradiction:
Ease of manufactureVSAdaptability or versatility

Solution Approach 1:

The patent changes the fundamental parameter of the reconstruction approach by abandoning smoothness hypotheses and instead using a point-based implicit function fitting method. This allows the system to handle arbitrary geometric structures including corners and non-regular shapes while maintaining computational feasibility through statistical moment-based fitting.

Inventive Principle:
Principle #35Parameter changes

2Adaptability or versatility

If implicit function fitting is used to increase adaptability to various structures, then the method can handle corner structures, but the accuracy of reconstruction is not satisfactory

Engineering Contradiction:
Improveability to handle corner structuresVSAvoidreconstruction accuracy
Core Design Contradiction:
Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent replaces traditional geometric fitting mechanisms with a statistical moment-based implicit function fitting approach. By using statistical moments to characterize point cloud distributions and fitting implicit functions based on these moments, the system achieves both high adaptability to various structures and improved reconstruction accuracy without requiring manual parameter tuning.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Device complexity

If traditional reconstruction methods are used, then the process may be simple, but the methods are sensitive to density changes, noise and outliers in point clouds

Engineering Contradiction:
Improvecomplexity of reconstruction methodVSAvoidrobustness to noise and outliers
Core Design Contradiction:
Device complexityVSReliability

Solution Approach 1:

The patent implements a self-service mechanism where the implicit function fitting process automatically adapts to varying point cloud densities and inherently filters noise and outliers through the statistical moment-based approach. The method self-regulates without requiring manual intervention for parameter tuning or preprocessing, achieving robustness while maintaining simplicity.

Inventive Principle:
Principle #25Self-service

4Manufacturing precision

If methods requiring manual parameter tuning are used, then accuracy may be improved for specific scenes, but the methods are not generic and require extensive manual adjustment

Engineering Contradiction:
Improvereconstruction accuracy for specific scenesVSAvoidneed for manual parameter tuning
Core Design Contradiction:
Manufacturing precisionVSEase of operation

Solution Approach 1:

The patent creates a universal implicit function fitting framework that automatically adapts to different scene types and point cloud characteristics without requiring manual parameter adjustment. The statistical moment-based approach provides a single generic method that functions effectively across diverse reconstruction scenarios, eliminating the need for scene-specific parameter tuning while maintaining high accuracy.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP3723052B13D reconstruction of a structure of a real scene
Publication Date: 2023.10.18 DASSAULT SYSTEMES SA
  • EP3723052B1 patent drawingFigure 1
  • EP3723052B1 patent drawingFigure 2
  • EP3723052B1 patent drawingFigure 3A~3B

AI summary

The invention notably relates to a computer-implemented method for 3D reconstruction of a structure of a real scene. The method comprises providing a 3D point cloud representing the structure. The method further comprises determining a closed triangulated surface representing a skin of the structure. The determining explores candidate closed triangulated surfaces each meshing at least a respective part of the 3D point cloud. The determining penalizes a high rank of the candidate closed triangulated surfaces according to a lexicographic order. The lexicographic order is based on a triangle order. The lexicographic order orders a first candidate closed triangulated surface having first triangles which are ordered according to a decreasing rank of the triangle order, relative to a second candidate closed triangulated surface having second triangles which are ordered according to a decreasing rank of the triangle order. The triangle order penalizes a triangle size. This constitutes an improved method for 3D reconstruction of a structure of a real scene.