Evolutionary computation approaches for shape modelling and fitting

被引:0
|
作者
Silva, S
Fayolle, PA
Vincent, J
Pauron, G
Rosenberger, C
Toinard, C
机构
[1] Univ Coimbra, Ctr Informat & Sistemas, P-3030 Coimbra, Portugal
[2] Univ Aizu, Software Dept, Fukushima 9658580, Japan
[3] Univ Orleans, ENSI Bourges, UPRES EA 2078, Lab Vis & Robot, F-18020 Bourges, France
[4] Univ Orleans, ENSI Bourges, CNRS FRE 2490, Lab Informat Fondamentale Orleans, F-18020 Bourges, France
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暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes and analyzes different evolutionary computation techniques for conjointly determining a model and its associated parameters. The context of 3D reconstruction of objects by a functional representation illustrates the ability of the proposed approaches to perform this task using real data, a set of 3D points on or near the surface of the real object. The final recovered model can then be used efficiently in further modelling, animation or analysis applications. The first approach is based on multiple genetic algorithms that find the correct model and parameters by successive approximations. The second approach is based on a standard strongly-typed implementation of genetic programming. This study shows radical differences between the results produced by each technique on a simple problem, and points toward future improvements to join the best features of both approaches.
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收藏
页码:144 / 155
页数:12
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