Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets

Patrick Mullen; Fernando de Goes; Mathieu Desbrun; David Cohen-Steiner; Pierre Alliez

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

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

Document type :

Journal articles

Domain :

Computer Science [cs] / Computational Geometry [cs.CG]

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https://hal.inria.fr/inria-00502473
Contributor : Pierre Alliez <>
Submitted on : Thursday, July 15, 2010 - 9:39:20 AM
Last modification on : Saturday, January 27, 2018 - 1:31:40 AM
Long-term archiving on : Thursday, December 1, 2016 - 8:28:37 AM

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Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets

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Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets

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