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Conference Papers Year : 2010

Feature Preserving Mesh Generation from 3D Point Clouds

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1
Nader Salman
  • Function : Author
  • PersonId : 862778
Mariette Yvinec
Quentin Mérigot

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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Dates and versions

inria-00497632 , version 1 (05-07-2010)

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  • HAL Id : inria-00497632 , version 1

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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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