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Feature-Preserving Surface Reconstruction and Simplification from Defect-Laden Point Sets

Julie Digne 1 David Cohen-Steiner 1 Pierre Alliez 1 Mathieu Desbrun 2 Fernando de Goes 2
1 GEOMETRICA - Geometric computing
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Saclay - Ile de France
Abstract : We propose a robust, feature-preserving surface reconstruction algorithm which turns a point set with noise and outliers into a low triangle-count simplicial complex. Our approach starts with a simplicial complex filtered from a 3D Delaunay triangulation of the input points. This initial approximation is iteratively simplified based on the optimal cost to transport the point set to the simplicial complex, both seen as measures (or mass distributions). Our optimal transport formulation allows the recovery of sharp features even in the presence of a large amount of outliers and/or noise in the input set.
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Submitted on : Monday, June 11, 2012 - 2:02:11 PM
Last modification on : Thursday, January 20, 2022 - 4:16:06 PM
Long-term archiving on: : Thursday, December 15, 2016 - 1:31:24 PM


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  • HAL Id : hal-00706712, version 1



Julie Digne, David Cohen-Steiner, Pierre Alliez, Mathieu Desbrun, Fernando de Goes. Feature-Preserving Surface Reconstruction and Simplification from Defect-Laden Point Sets. [Research Report] RR-7991, INRIA. 2012, pp.23. ⟨hal-00706712⟩



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