A Delaunay refinement algorithm for quality 2-dimensional mesh generation
SODA '93 Selected papers from the fourth annual ACM SIAM symposium on Discrete algorithms
Selected papers from the 12th annual symposium on Computational Geometry
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Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator
FCRC '96/WACG '96 Selected papers from the Workshop on Applied Computational Geormetry, Towards Geometric Engineering
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Mesh generation and geometric persistent homology
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Computer Graphics Forum
Delaunay Mesh Generation
A new approach to output-sensitive voronoi diagrams and delaunay triangulations
Proceedings of the twenty-ninth annual symposium on Computational geometry
Improving spatial coverage while preserving the blue noise of point sets
Computer-Aided Design
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We present a new algorithm that produces a well-spaced superset of points conforming to a given input set in any dimension with guaranteed optimal output size. We also provide an approximate Delaunay graph on the output points. Our algorithm runs in expected time O(2O(d)(n log n + m)), where n is the input size, m is the output point set size, and d is the ambient dimension. The constants only depend on the desired element quality bounds. To gain this new efficiency, the algorithm approximately maintains the Voronoi diagram of the current set of points by storing a superset of the Delaunay neighbors of each point. By retaining quality of the Voronoi diagram and avoiding the storage of the full Voronoi diagram, a simple exponential dependence on d is obtained in the running time. Thus, if one only wants the approximate neighbors structure of a refined Delaunay mesh conforming to a set of input points, the algorithm will return a size 2O(d)m graph in 2O(d)(n log n + m) expected time. If m is superlinear in n, then we can produce a hierarchically well-spaced superset of size 2O(d)n in 2O(d)n log n expected time.