Planar Minimization Diagrams via Subdivision with Applications to Anisotropic Voronoi Diagrams
Let X = {f1, …, fn} be a set of scalar functions of the form fi : ℝ2 → ℝ which satisfy some natural properties. We describe a subdivision algorithm for computing a clustered ε‐isotopic approximation of the minimization diagram of X. By exploiting soft predicates and clustering of Voronoi vertices, o...
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Published in | Computer graphics forum Vol. 35; no. 5; pp. 229 - 247 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.08.2016
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Subjects | |
Online Access | Get full text |
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Summary: | Let X = {f1, …, fn} be a set of scalar functions of the form fi : ℝ2 → ℝ which satisfy some natural properties. We describe a subdivision algorithm for computing a clustered ε‐isotopic approximation of the minimization diagram of X. By exploiting soft predicates and clustering of Voronoi vertices, our algorithm is the first that can handle arbitrary degeneracies in X, and allow scalar functions which are piecewise smooth, and not necessarily semi‐algebraic.
We apply these ideas to the computation of anisotropic Voronoi diagram of polygonal sets; this is a natural generalization of anisotropic Voronoi diagrams of point sites, which extends multiplicatively weighted Voronoi diagrams. We implement a prototype of our anisotropic algorithm and provide experimental results. |
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Bibliography: | ArticleID:CGF12979 istex:FE3E80C9E7922B52CEDE558E09766C85AE01521A ark:/67375/WNG-HG73N5NS-8 Chee and Huck are supported by NSF Grant #CCF‐1423228. Evanthia is supported by SNSF #20GG21‐134355, #200021E‐154387. SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0167-7055 1467-8659 |
DOI: | 10.1111/cgf.12979 |