Reconstruction of symmetric models composed of analytic curves and surfaces from point cloud

This paper presents a method to reconstruct symmetric geometric models from point cloud with inherent symmetric structure. Symmetry types commonly found in engineering parts, i.e., translational, reflectional and rotational symmetries are considered. The reconstruction problem is formulated as a con...

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Bibliographic Details
Published inJournal of Zhejiang University. A. Science Vol. 9; no. 10; pp. 1351 - 1362
Main Authors Wang, Qing, Zhu, Wei-dong, Ke, Ying-lin
Format Journal Article
LanguageEnglish
Published Hangzhou Zhejiang University Press 01.10.2008
State Key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China
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Summary:This paper presents a method to reconstruct symmetric geometric models from point cloud with inherent symmetric structure. Symmetry types commonly found in engineering parts, i.e., translational, reflectional and rotational symmetries are considered. The reconstruction problem is formulated as a constrained optimization, where the objective function is the sum of squared distances of points to the model, and constraints are enforced to keep geometric relationships in the model. First, the explicit representations of symmetric models are presented. Then, by using the concept ofparameterized points (where the coordinate components are represented as functions rather than constants), the distances of points to symmetric models are deduced. With these distance functions, symmetry information, for both 2D and 3D models, is uniformly represented in the process of reconstruction. The constrained optimization problem is solved by a standard nonlinear optimization method. Owing to the explicit representation of symmetry information, the computational complexity of our method is reduced greatly. Finally, examples are given to demonstrate the application of the proposed method.
Bibliography:TP391.7
Reverse engineering, Model reconstruction, Constrained optimization, Symmetry
33-1236/O4
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.A0820324