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International Conference on Evolutionary Programming

EP 1998: Evolutionary Programming VII pp 199–208Cite as

Genetic search for object identification

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1447))

Abstract

We attack the problem of recognizing real, planar objects from two-dimensional, intensity images taken from arbitrary viewpoints using genetic algorithms. More specifically, we use genetic algorithms to search for a geometric mapping that brings subsets of points comprising the model and subsets of points comprising the scene into alignment. The genetic algorithm searches the image space and we compare different encodings and operators on a set of three increasingly complex scenes. Our preliminary results are promising with exact and near exact matches being found reliably and quickly.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Nevada, 89557, Reno

    Sushil J. Louis, George Bebis, Satish Uthiram & Yaakov Varol

Authors
  1. Sushil J. Louis
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  2. George Bebis
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  3. Satish Uthiram
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  4. Yaakov Varol
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Editor information

V. W. Porto N. Saravanan D. Waagen A. E. Eiben

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© 1998 Springer-Verlag Berlin Heidelberg

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Louis, S.J., Bebis, G., Uthiram, S., Varol, Y. (1998). Genetic search for object identification. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040773

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  • DOI: https://doi.org/10.1007/BFb0040773

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64891-8

  • Online ISBN: 978-3-540-68515-9

  • eBook Packages: Springer Book Archive

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