Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets

Patrick Mullen 1 Fernando De Goes 1 Mathieu Desbrun 1 David Cohen-Steiner 2 Pierre Alliez 2
1 CS CALTECH - Computer Science Department
2 GEOMETRICA - Geometric computing
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Saclay - Ile de France
Abstract : We propose a modular framework for robust 3D reconstruction from unorganized, unoriented, noisy, and outlierridden geometric data. We gain robustness and scalability over previous methods through an unsigned distance approximation to the input data followed by a global stochastic signing of the function. An isosurface reconstruction is finally deduced via a sparse linear solve. We show with experiments on large, raw, geometric datasets that this approach is scalable while robust to noise, outliers, and holes. The modularity of our approach facilitates customization of the pipeline components to exploit specific idiosyncracies of datasets, while the simplicity of each component leads to a straightforward implementation.
Mots-clés : surface reconstruction noise robust outlier robust
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Article dans une revue
Computer Graphics Forum, Wiley, 2010, Symposium on Geometry Processing, 29 (5), pp.1733-1741
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Soumis le : jeudi 15 juillet 2010 - 09:39:20
Dernière modification le : samedi 27 janvier 2018 - 01:31:40
Document(s) archivé(s) le : jeudi 1 décembre 2016 - 08:28:37

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Patrick Mullen, Fernando De Goes, Mathieu Desbrun, David Cohen-Steiner, Pierre Alliez. Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets. Computer Graphics Forum, Wiley, 2010, Symposium on Geometry Processing, 29 (5), pp.1733-1741. 〈inria-00502473〉

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