Object modeling from multiple images using genetic algorithms

Hideo Saito, Masayuki Mori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


This paper describes an application of genetic algorithms (GAs) to modeling of multiple objects from CCD images. Shape modeling is a very important issue for shape recognition for robot vision, representing 3-D shapes in the virtual world, and so on. In this paper, we propose a method for object modeling from multiple view images using genetic algorithms (GAs). In this method, similarity between the model and the image at each view angle is evaluated. The model having the maximum evaluation is found by GAs. In the proposed method, a sharing scheme is used for finding multiple solutions efficiently. Some results of object modeling experiments from synthetic and real multiple view images demonstrate that the proposed method can robustly generate models by using GAs.

Original languageEnglish
Title of host publicationTrack D
Subtitle of host publicationParallel and Connectionist Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)081867282X, 9780818672828
Publication statusPublished - 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: 1996 Aug 251996 Aug 29

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Other13th International Conference on Pattern Recognition, ICPR 1996

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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