Abstract
In this paper, we propose an object tracking method on video sequence using an extension of Particle Swarm Optimization (PSO) algorithm, which is inspired by the behavior of bird flocking and fish schooling. PSO is a useful algorithm because of its easy-to-understand algorithm, rapid exploration and easy implementation. In general, PSO is applied to optimization of static problem, and thus it is difficult to use PSO for the object tracking problems where the target moves in real time. To overcome this difficulty, we introduce two extensions. To preserve the feature of PSO, it is important to extend algorithm with the simple way. The first extension is to introduce parameters so that the individuals do not converge completely. The second one is a re-initialization technique to track object between each frame-image smoothly. With these extensions, we achieve a high efficiency real time object tracking algorithm on video sequence. We demonstrate the effectiveness and practical utility of our method through some simulations and experiments.
| Original language | English |
|---|---|
| Pages (from-to) | 2005-2012 |
| Number of pages | 8 |
| Journal | Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C |
| Volume | 75 |
| Issue number | 755 |
| Publication status | Published - 2009 Jul |
| Externally published | Yes |
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Keywords
- Mobile robot
- Object tracking
- Particle swarm optimization
- Robot vision
- Video image processing
ASJC Scopus subject areas
- Mechanical Engineering
- Mechanics of Materials
- Industrial and Manufacturing Engineering
Cite this
A study of extended PSO algorithm for video image processing and its application to a mobile robot. / Kobayashi, Tomoaki; Keita, Nakagawa; Joe, Imae; Zhai, Guisheng.
In: Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, Vol. 75, No. 755, 07.2009, p. 2005-2012.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A study of extended PSO algorithm for video image processing and its application to a mobile robot
AU - Kobayashi, Tomoaki
AU - Keita, Nakagawa
AU - Joe, Imae
AU - Zhai, Guisheng
PY - 2009/7
Y1 - 2009/7
N2 - In this paper, we propose an object tracking method on video sequence using an extension of Particle Swarm Optimization (PSO) algorithm, which is inspired by the behavior of bird flocking and fish schooling. PSO is a useful algorithm because of its easy-to-understand algorithm, rapid exploration and easy implementation. In general, PSO is applied to optimization of static problem, and thus it is difficult to use PSO for the object tracking problems where the target moves in real time. To overcome this difficulty, we introduce two extensions. To preserve the feature of PSO, it is important to extend algorithm with the simple way. The first extension is to introduce parameters so that the individuals do not converge completely. The second one is a re-initialization technique to track object between each frame-image smoothly. With these extensions, we achieve a high efficiency real time object tracking algorithm on video sequence. We demonstrate the effectiveness and practical utility of our method through some simulations and experiments.
AB - In this paper, we propose an object tracking method on video sequence using an extension of Particle Swarm Optimization (PSO) algorithm, which is inspired by the behavior of bird flocking and fish schooling. PSO is a useful algorithm because of its easy-to-understand algorithm, rapid exploration and easy implementation. In general, PSO is applied to optimization of static problem, and thus it is difficult to use PSO for the object tracking problems where the target moves in real time. To overcome this difficulty, we introduce two extensions. To preserve the feature of PSO, it is important to extend algorithm with the simple way. The first extension is to introduce parameters so that the individuals do not converge completely. The second one is a re-initialization technique to track object between each frame-image smoothly. With these extensions, we achieve a high efficiency real time object tracking algorithm on video sequence. We demonstrate the effectiveness and practical utility of our method through some simulations and experiments.
KW - Mobile robot
KW - Object tracking
KW - Particle swarm optimization
KW - Robot vision
KW - Video image processing
UR - http://www.scopus.com/inward/record.url?scp=70349647750&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349647750&partnerID=8YFLogxK
M3 - Article
VL - 75
SP - 2005
EP - 2012
JO - Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
JF - Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
SN - 0387-5024
IS - 755
ER -