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Proceedings Paper

Object and pose recognition with cellular genetic algorithms
Author(s): Timo Mantere
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Paper Abstract

We have studied the use of cellular automata and cellular genetic algorithms for the object recognition, pose recognition, and image classification problems. The cellular genetic algorithm is a genetic algorithm that has some similarities with cellular automata. The preliminary results seem to support the hypothesis that in principle this kind of object and pose recognition and image classification method works relatively well. The problem with the proposed method is a large amount of calculations needed when we are testing the unknown object against the objects in the comparison set.

Paper Details

Date Published: 10 September 2007
PDF: 10 pages
Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640N (10 September 2007); doi: 10.1117/12.733960
Show Author Affiliations
Timo Mantere, Univ. of Vaasa (Finland)


Published in SPIE Proceedings Vol. 6764:
Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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