PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds (Unknown language)

in Symposium on Geometry Processing 2017- Posters; 11-12
Symposium on Geometry Processing 2017- Posters

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.

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Table of contents conference proceedings

The table of contents of the conference proceedings is generated automatically, so it can be incomplete, although all articles are available in the TIB.

1
Sequentially-Defined Compressed Modes via ADMM
Houston, Kevin | 2017
3
DepthCut: Improved Depth Edge Estimation Using Multiple Unreliable Channels
Guerrero, Paul / Winnemöller, Holger / Li, Wilmot / Mitra, Niloy J. | 2017
5
Localized Manifold Harmonics for Spectral Shape Analysis
Melzi, Simone / Rodolà, Emanuele / Castellani, Umberto / Bronstein, Michael M. | 2017
7
A Primal-to-Primal Discretization of Exterior Calculus on Polygonal Meshes
Ptackova, Lenka / Velho, Luiz | 2017
9
Schrödinger Operator for Sparse Approximation of 3D Meshes
Choukroun, Yoni / Pai, Gautam / Kimmel, Ron | 2017
11
PCR: A Geometric Cocktail for Triangulating Point Clouds Beautifully Without Angle Bounds
Leitão, Gonçalo N. V. / Gomes, Abel J. P. | 2017

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