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Journal Articles IEEE Transactions on Visualization and Computer Graphics Year : 2017

Error-Bounded and Feature Preserving Surface Remeshing with Minimal Angle Improvement

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Abstract

The typical goal of surface remeshing consists in finding a mesh that is (1) geometrically faithful to the original geometry, (2) as coarse as possible to obtain a low-complexity representation and (3) free of bad elements that would hamper the desired application. In this paper, we design an algorithm to address all three optimization goals simultaneously. The user specifies desired bounds on approximation error , minimal interior angle and maximum mesh complexity N (number of vertices). Since such a desired mesh might not even exist, our optimization framework treats only the approximation error bound as a hard constraint and the other two criteria as optimization goals. More specifically, we iteratively perform carefully prioritized local operators, whenever they do not violate the approximation error bound and improve the mesh otherwise. Our optimization framework greedily searches for the coarsest mesh with minimal interior angle above and approximation error bounded by . Fast runtime is enabled by a local approximation error estimation, while implicit feature preservation is obtained by specifically designed vertex relocation operators. Experiments show that our approach delivers high-quality meshes with implicitly preserved features and better balances between geometric fidelity, mesh complexity and element quality than the state-of-the-art.
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Format : Figure, Image
Origin : Files produced by the author(s)
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Dates and versions

hal-01549584 , version 1 (19-09-2017)

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Kaimo Hu, Dong-Ming Yan, David Bommes, Pierre Alliez, Bedrich Benes. Error-Bounded and Feature Preserving Surface Remeshing with Minimal Angle Improvement. IEEE Transactions on Visualization and Computer Graphics, 2017, ⟨10.1109/TVCG.2016.2632720⟩. ⟨hal-01549584⟩
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