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2008 International Conference on Computational Sciences and Its Applications
Automatically Approximating 3D Points with Co-Axisal Objects
June 30-July 03
ISBN: 978-0-7695-3243-1
In this paper, we investigate the problem of approximating a set S of 3D points with co-axisal objects typically from CAD/CAM (namely, cylindrical segments, cones and conical frustums). The objective is to minimize the sume of volumes of these objects (as well as the number of objects used). The general problem when the objects can have arbitrary axes is strongly NP-hard as a cylindrical segment, a cone and a conical frustum can all degenerate into a line segment. We present a general algorithm which combines a neat doubling search method to decompose S into desired subsets (or components). For each subset S, we present a unified practical approximation algorithm for minimizing the volume of the cone (conical frustum, or cylindrical segment) which encloses points in S. Preliminary empirical results indicate that the algorithm is in fact very accurate.
Index Terms:
Geometric modeling, Approximation algorithms, Smallest enclosing cone, Smallest enclosing conical frustum, Smallest enclosing cylindrical segment
Citation:
Russell Tempero, Sergey Bereg, Xiangxu Meng, Changhe Tu, Chenglei Yang, Binhai Zhu, "Automatically Approximating 3D Points with Co-Axisal Objects," iccsa, pp.373-381, 2008 International Conference on Computational Sciences and Its Applications, 2008
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