Feature Preserving Mesh Generation from 3D Point Clouds

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2010
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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 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.
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@article{
10.1111:j.1467-8659.2010.01771.x
, journal = {Computer Graphics Forum}, title = {{
Feature Preserving Mesh Generation from 3D Point Clouds
}}, author = {
Nader Salman
and
Mariette Yvinec
and
Quentin Merigot
}, year = {
2010
}, publisher = {}, DOI = {
10.1111/j.1467-8659.2010.01771.x
} }
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