Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking
Joint Authors
Wang, Yanjiang
Qi, Yujuan
Li, Yongping
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper.
Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience.
A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration.
Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object.
It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods.
American Psychological Association (APA)
Wang, Yanjiang& Qi, Yujuan& Li, Yongping. 2013. Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1012893
Modern Language Association (MLA)
Wang, Yanjiang…[et al.]. Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking. The Scientific World Journal No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1012893
American Medical Association (AMA)
Wang, Yanjiang& Qi, Yujuan& Li, Yongping. Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1012893
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1012893