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Feature Preserving Mesh Generation from 3D Point Clouds
Author(s) -
Salman Nader,
Yvinec Mariette,
Merigot Quentin
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2010.01771.x
Subject(s) - point cloud , polygon mesh , computer science , delaunay triangulation , feature (linguistics) , surface reconstruction , algorithm , piecewise , mesh generation , voronoi diagram , surface (topology) , artificial intelligence , computer vision , mathematics , computer graphics (images) , geometry , mathematical analysis , linguistics , philosophy , physics , finite element method , thermodynamics
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 extract 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.