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Visual Tracking Using an Insect Vision Embedded Particle Filter
Joint Authors
Zhao, Qingjie
Guo, Wei
Gu, Dongbing
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-06
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Particle filtering (PF) based object tracking algorithms have drawn great attention from lots of scholars.
The core of PF is to predict the possible location of the target via the state transition model.
One commonly adopted approach is resorting to prior motion cues under the smooth motion assumption, which performs well when the target moves with a relatively stable velocity.
However, it would possibly fail if the target is undergoing abrupt motion.
To address this problem, inspired by insect vision, we propose a simple yet effective visual tracking framework based on PF.
Utilizing the neuronal computational model of the insect vision, we estimate the motion of the target in a novel way so as to refine the position state of propagated particles using more accurate transition mode.
Furthermore, we design a novel sample optimization framework where local and global search strategies are jointly used.
In addition, we propose a new method to monitor long duration severe occlusion and we could recover the target.
Experiments on publicly available benchmark video sequences demonstrate that the proposed tracking algorithm outperforms the state-of-the art methods in challenging scenarios, especially for tracking target which is undergoing abrupt motion or fast movement.
American Psychological Association (APA)
Guo, Wei& Zhao, Qingjie& Gu, Dongbing. 2015. Visual Tracking Using an Insect Vision Embedded Particle Filter. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1074170
Modern Language Association (MLA)
Guo, Wei…[et al.]. Visual Tracking Using an Insect Vision Embedded Particle Filter. Mathematical Problems in Engineering No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1074170
American Medical Association (AMA)
Guo, Wei& Zhao, Qingjie& Gu, Dongbing. Visual Tracking Using an Insect Vision Embedded Particle Filter. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1074170
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074170