Incremental boundary evaluation using inference of edge classifications

Author

Miller, James R.

Author_Institution

Dept. of Comput. Sci., Kansas Univ., Lawrence, KS, USA

Volume

13

Issue

1

fYear

1993

Firstpage

71

Lastpage

78

Abstract

An incremental boundary-evaluation algorithm that exploits adjacency information in B-reps to minimize the number of explicit edge classifications required is presented. Evaluations of the implemented algorithm show that it performs reliably and well, although global optimization schemes could increase performance significantly. The steps of the algorithm, which include self-edge partitioning, cross-edge self-edge (CESE) classification, inference of self-edge classifications, and checking for split and merged shells, are discussed.<>

Keywords

computational geometry; optimisation; solid modelling; B-reps; CESE; adjacency information; cross-edge self-edge; explicit edge classifications; global optimization schemes; implemented algorithm; incremental boundary-evaluation algorithm; inference; merged shells; self-edge classifications; self-edge partitioning; Algorithm design and analysis; Binary trees; Data structures; Education; Geometry; Logic design; Merging; Solid modeling; Tree data structures; Tree graphs;

fLanguage

English

Journal_Title

Computer Graphics and Applications, IEEE

Publisher

ieee

ISSN

0272-1716

Type

jour

DOI

10.1109/38.180120

Filename

180120