Surface Reconstruction from 3D Point Data with a Genetic Programming/Evolution Strategy hybrid

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Date

2001-10-16

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Universität Dortmund

Abstract

Surface reconstruction is a hard key problem in the industrial domain of computer-aided design (CAD) applications. A physical object, like a workpiece, must be represented in some standard CAD object description format such that its representation can be efficiently used in a CAD process like redesign. To that end, a digitizing process represents the object surface as a weakly-structured discrete and digitized set of 3D points. Surface reconstruction attempts to transform this representation into an efficient CAD representation. Certain classic approaches produce inefficient reconstructions of surface areas that do not correspond to construction logic. Here, a new reconstruction principle in form of a computational-intelligence-based software system is presented that yields logical and efficient representations.

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Keywords

computational intelligence (CI), computer-aided design (cad), constructive solid geometry (CSG), digitized point data, evolution strategy (ES), genetic programming (GP), incremental optimization, interactive evolution, multi-criteria optimization, pattern recognition, structure evolution, surface reconstruction

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