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Feature Preserving Mesh Generation from 3D Point Clouds

Nader Salman 1 Mariette Yvinec 1 Quentin Mérigot 1
1 GEOMETRICA - Geometric computing
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Saclay - Ile de France
Abstract : We address the problem of generating quality surface triangle meshes from 3D point clouds sampled on piecewise smooth surfaces. Using a feature detection process based on the covariance matrices of Voronoi cells, we first ex- tract from the point cloud a set of sharp features. Our algorithm also runs on the input point cloud a reconstruction process, such as Poisson reconstruction, providing an implicit surface. A feature preserving variant of a Delaunay refinement process is then used to generate a mesh approximating the implicit surface and containing a faithful representation of the extracted sharp edges. Such a mesh provides an enhanced trade-off between accuracy and mesh complexity. The whole process is robust to noise and made versatile through a small set of parameters which govern the mesh sizing, approximation error and shape of the elements. We demonstrate the effectiveness of our method on a variety of models including laser scanned datasets ranging from indoor to outdoor scenes.
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Submitted on : Monday, July 5, 2010 - 2:32:17 PM
Last modification on : Tuesday, December 8, 2020 - 9:58:03 AM
Long-term archiving on: : Tuesday, October 23, 2012 - 9:51:30 AM


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  • HAL Id : inria-00497632, version 1



Nader Salman, Mariette Yvinec, Quentin Mérigot. Feature Preserving Mesh Generation from 3D Point Clouds. Computer Graphics Forum, Jul 2010, Lyon, France. pp.1623-1632. ⟨inria-00497632⟩



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