Delaunay triangulation programs on surface data

Authors:
Sunghee Choi;Nina Amenta
Affiliations:
The University of Texas at Austin;The University of Texas at Austin
Venue:
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Year:
2002

Citing 5
Cited 5

Higher-dimensional Voronoi diagrams in linear expected time

Discrete & Computational Geometry
Fast randomized point location without preprocessing in two- and three-dimensional Delaunay triangulations

Proceedings of the twelfth annual symposium on Computational geometry
Improved incremental randomized Delaunay triangulation

Proceedings of the fourteenth annual symposium on Computational geometry
Nice point sets can have nasty Delaunay triangulations

SCG '01 Proceedings of the seventeenth annual symposium on Computational geometry
Four Results on Randomized Incremental Constructions

STACS '92 Proceedings of the 9th Annual Symposium on Theoretical Aspects of Computer Science

The Delaunay tetrahedralization from Delaunay triangulated surfaces

Proceedings of the eighteenth annual symposium on Computational geometry
A linear bound on the complexity of the delaunay triangulation of points on polyhedral surfaces

Proceedings of the seventh ACM symposium on Solid modeling and applications
Incremental constructions con BRIO

Proceedings of the nineteenth annual symposium on Computational geometry
Meshing skin surfaces with certified topology

Computational Geometry: Theory and Applications
A surface reconstruction algorithm using weighted alpha shapes

FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Delaunay triangulation of a set of points in 3D can have size Θ(n2) in the worst case, but this is rarely if ever observed in practice. We compare three production-quality Delaunay triangulation programs on some 'real-world' sets of points lying on or near 2D surfaces.