Feature Preserving Mesh Generation from 3D Point Clouds

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dc.contributor.authorNader Salmanen_US
dc.contributor.authorMariette Yvinecen_US
dc.contributor.authorQuentin Merigoten_US
dc.date.accessioned2015-02-23T17:15:37Z
dc.date.available2015-02-23T17:15:37Z
dc.date.issued2010en_US
dc.description.abstractWe 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.en_US
dc.description.number5en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2010.01771.xen_US
dc.identifier.pages1623-1632en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v29i5pp1623-1632en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v29i5pp1623-1632
dc.titleFeature Preserving Mesh Generation from 3D Point Cloudsen_US
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29-Issue 5
SGP10: Eurographics Symposium on Geometry Processing