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Article: Surface registration using a dynamic genetic algorithm

TitleSurface registration using a dynamic genetic algorithm
Authors
Issue Date2004
Citation
Pattern Recognition, 2004, v. 37 n. 1, p. 105-117 How to Cite?
AbstractRobust and fast free-form surface registration is a useful technique in various areas such as object recognition and 3D model reconstruction for animation. Notably, an object model can be constructed, in principle, by surface registration and integration of range images of the target object from different views. In this paper, we propose to formulate the surface registration problem as a high dimensional optimization problem, which can be solved by a genetic algorithm (GA) (Genetic Algorithms in Search Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989). The performance of the GA for surface registration is highly dependent on its speed in evaluating the fitness function. A novel GA with a new fitness function and a new genetic operator is proposed. It can compute an optimal registration 1000 times faster than a conventional GA. The accuracy, speed and the robustness of the proposed method are verified by a number of real experiments. © 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/196643
ISSN
2015 Impact Factor: 3.399
2015 SCImago Journal Rankings: 2.051
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChow, CK-
dc.contributor.authorTsui, HT-
dc.contributor.authorLee, T-
dc.date.accessioned2014-04-24T02:10:30Z-
dc.date.available2014-04-24T02:10:30Z-
dc.date.issued2004-
dc.identifier.citationPattern Recognition, 2004, v. 37 n. 1, p. 105-117-
dc.identifier.issn0031-3203-
dc.identifier.urihttp://hdl.handle.net/10722/196643-
dc.description.abstractRobust and fast free-form surface registration is a useful technique in various areas such as object recognition and 3D model reconstruction for animation. Notably, an object model can be constructed, in principle, by surface registration and integration of range images of the target object from different views. In this paper, we propose to formulate the surface registration problem as a high dimensional optimization problem, which can be solved by a genetic algorithm (GA) (Genetic Algorithms in Search Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989). The performance of the GA for surface registration is highly dependent on its speed in evaluating the fitness function. A novel GA with a new fitness function and a new genetic operator is proposed. It can compute an optimal registration 1000 times faster than a conventional GA. The accuracy, speed and the robustness of the proposed method are verified by a number of real experiments. © 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.-
dc.languageeng-
dc.relation.ispartofPattern Recognition-
dc.titleSurface registration using a dynamic genetic algorithm-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S0031-3203(03)00222-X-
dc.identifier.scopuseid_2-s2.0-0242406172-
dc.identifier.volume37-
dc.identifier.issue1-
dc.identifier.spage105-
dc.identifier.epage117-
dc.identifier.isiWOS:000186764100008-

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