Abstract
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 language | English |
|---|---|
| Title of host publication | Proceedings - International Conference on Pattern Recognition |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 669-673 |
| Number of pages | 5 |
| Volume | 4 |
| ISBN (Print) | 081867282X, 9780818672828 |
| DOIs | |
| Publication status | Published - 1996 |
| Event | 13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria Duration: 1996 Aug 25 → 1996 Aug 29 |
Other
| Other | 13th International Conference on Pattern Recognition, ICPR 1996 |
|---|---|
| Country | Austria |
| City | Vienna |
| Period | 96/8/25 → 96/8/29 |
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ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
Cite this
Object modeling from multiple images using genetic algorithms. / Saito, Hideo; Mori, Masayuki.
Proceedings - International Conference on Pattern Recognition. Vol. 4 Institute of Electrical and Electronics Engineers Inc., 1996. p. 669-673 547649.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Object modeling from multiple images using genetic algorithms
AU - Saito, Hideo
AU - Mori, Masayuki
PY - 1996
Y1 - 1996
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84898775649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84898775649&partnerID=8YFLogxK
U2 - 10.1109/ICPR.1996.547649
DO - 10.1109/ICPR.1996.547649
M3 - Conference contribution
AN - SCOPUS:84898775649
SN - 081867282X
SN - 9780818672828
VL - 4
SP - 669
EP - 673
BT - Proceedings - International Conference on Pattern Recognition
PB - Institute of Electrical and Electronics Engineers Inc.
ER -