Authors: Mehnen, Jörn
Weinert, Klaus
Title: A Comparison of Point Data Selection Schemes for Evolutionary Surface Reconstructions
Language (ISO): en
Abstract: This article presents a study of the application of Computational Intelligence (CI) methods to the problem of optimal surface reconstruction using triangulations and NURBS (Non-Uniform Rational B-Splines) surface approximations on digitized point data. In mechanical engineering surface reconstructions are used to transform physical objects into mathematical representations for computer aided design purposes. In order to record the geometrical shape of the objects, tactile or optical sensors generate point sets with a huge number of sample points. The number and distribution of these points are decisive for the quality and computational efficiency of the numerical surface representations. Triangulations and NURBS are widely used in CAD/CAM-applications, because they belong to a class of very exible discrete interpolation and approximation methods. In order to verify the suitability of surface model independent point selection schemes and to find model dependent sampling point distributions, optimal surface reconstructions are used.
Subject Headings: evolutionary algorithms
NURBS surface approximation
point selection schemes
surface reconstruction
Issue Date: 2001-10-17
Provenance: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 531

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