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Tracking Full-Body Motion of Multiple Fish with Midline Subspace Constrained Multicue Optimization
Joint Authors
Liu, Xiang
Zhu, Pei Ru
Liu, Ye
Zhao, Jing Wen
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-06-24
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Capturing the body motion of fish has been gaining considerable attention from scientists of various fields.
In this paper, we propose a method which is able to track the full-body motion of multiple fish with frequent interactions.
We firstly propose to model the midline subspace of a fish body which gives a compact low-dimensional representation of the complex shape and motion.
Then we propose a particle swarm-based optimization framework whose objective function takes into account multiple sources of information.
The proposed multicue objective function is able to describe the details of fish appearance and is also effective through mutual occlusions.
Excessive experimental results have demonstrated the effectiveness and robustness of the proposed method.
American Psychological Association (APA)
Liu, Xiang& Zhu, Pei Ru& Liu, Ye& Zhao, Jing Wen. 2019. Tracking Full-Body Motion of Multiple Fish with Midline Subspace Constrained Multicue Optimization. Scientific Programming،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1210722
Modern Language Association (MLA)
Liu, Xiang…[et al.]. Tracking Full-Body Motion of Multiple Fish with Midline Subspace Constrained Multicue Optimization. Scientific Programming No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1210722
American Medical Association (AMA)
Liu, Xiang& Zhu, Pei Ru& Liu, Ye& Zhao, Jing Wen. Tracking Full-Body Motion of Multiple Fish with Midline Subspace Constrained Multicue Optimization. Scientific Programming. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1210722
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210722