PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds

Leitão, Gonçalo N. V.; Gomes, Abel J. P.

PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds

Files

011-012.pdf (418.71 KB)

Date

2017

Authors

Leitão, Gonçalo N. V.
Gomes, Abel J. P.

Publisher

The Eurographics Association

Abstract

Reconstructing a triangulated surface from a point cloud through a mesh growing algorithm is a difficult problem, in largely because they use bounds for the admissible dihedral angle to decide on the next triangle to be attached to the mesh front. This paper proposes a solution to this problem by combining three geometric properties: proximity, co-planarity, and regularity; hence, the PCR cocktail. The PCR cocktail-based algorithm works well even for point clouds with non-uniform point density, holes, high curvature regions, creases, apices, and noise.

        @inproceedings{10.2312:sgp.20171206
,
booktitle = {Symposium on Geometry Processing 2017- Posters
},
editor = {Jakob Andreas Bærentzen and Klaus Hildebrandt
},
title = {{PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds
}},
author = {Leitão, Gonçalo N. V. and 
Gomes, Abel J. P.
},
year = {2017
},
publisher = {The Eurographics Association
},
ISSN = {1727-8384
},
ISBN = {978-3-03868-047-5
},
DOI = {10.2312/sgp.20171206
}
}