AHD: The alternate hierarchical decomposition of nonconvex polytopes (generalization of a convex polytope based spatial data model)

Rizwan Bulbul*, Andrew U. Frank

*Korrespondierende/r Autor/in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

Robust convex decomposition, RCD, of polytopes is the convex decomposition of nonconvex polytopes using algorithms whose implementation is based on arbitrary precision arithmetic. Decomposing nonconvex polytopes using RCD can make the data representation model consistent enabling generalization with level of detail. Our approach, alternate hierarchical decomposition, AHD, for the decomposition of nonconvex polytopes with arbitrary genus, is a recursive approach whose implementation is robust, efficient and scalable to any dimension. Our approach decomposes the given nonconvex polytope with arbitrary genus into a set of component convex hulls, which are represented hierarchically in a tree structure, convex hull tree, CHT.
Originalspracheenglisch
Titel2009 17th International Conference on Geoinformatics
Seiten1-6
DOIs
PublikationsstatusVeröffentlicht - 12 Aug 2009
Extern publiziertJa
Veranstaltung17th International Conference on Geoinformatics - CSISS, George Mason University, Fairfax, USA / Vereinigte Staaten
Dauer: 12 Aug 200914 Aug 2009
https://ieeexplore.ieee.org/xpl/conhome/5286203/proceeding

Konferenz

Konferenz17th International Conference on Geoinformatics
Kurztitelgeoinfotmatics2009
LandUSA / Vereinigte Staaten
OrtFairfax
Zeitraum12/08/0914/08/09
Internetadresse

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