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Part-Based Visual Tracking via Online Weighted P-N Learning
Joint Authors
Fan, Heng
Xu, Jun
Liao, Honghong
Xiang, Jinhai
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
We propose a novel part-based tracking algorithm using online weighted P-N learning.
An online weighted P-N learning method is implemented via considering the weight of samples during classification, which improves the performance of classifier.
We apply weighted P-N learning to track a part-based target model instead of whole target.
In doing so, object is segmented into fragments and parts of them are selected as local feature blocks (LFBs).
Then, the weighted P-N learning is employed to train classifier for each local feature block (LFB).
Each LFB is tracked through the corresponding classifier, respectively.
According to the tracking results of LFBs, object can be then located.
During tracking process, to solve the issues of occlusion or pose change, we use a substitute strategy to dynamically update the set of LFB, which makes our tracker robust.
Experimental results demonstrate that the proposed method outperforms the state-of-the-art trackers.
American Psychological Association (APA)
Fan, Heng& Xiang, Jinhai& Xu, Jun& Liao, Honghong. 2014. Part-Based Visual Tracking via Online Weighted P-N Learning. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1049476
Modern Language Association (MLA)
Fan, Heng…[et al.]. Part-Based Visual Tracking via Online Weighted P-N Learning. The Scientific World Journal No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1049476
American Medical Association (AMA)
Fan, Heng& Xiang, Jinhai& Xu, Jun& Liao, Honghong. Part-Based Visual Tracking via Online Weighted P-N Learning. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1049476
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049476