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
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.
Document type :
Journal articles
Complete list of metadatas

Cited literature [17 references]  Display  Hide  Download


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

Files

signing.pdf
Explicit agreement for this submission

Identifiers

  • HAL Id : inria-00502473, version 1

Collections

Citation

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⟩

Share

Metrics

Record views

765

Files downloads

663