Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Many modern visual tracking algorithms incorporate spatial pooling, max pooling, or average pooling, which is to achieve invariance to feature transformations and better robustness to occlusion, illumination change, and position variation.
In this paper, max-average pooling method and Weight-selection strategy are proposed with a hybrid framework, which is combined with sparse representation and particle filter, to exploit the spatial information of an object and make good compromises to ensure the correctness of the results in this framework.
Challenges can be well considered by the proposed algorithm.
Experimental results demonstrate the effectiveness and robustness of the proposed algorithm compared with the state-of-the-art methods on challenging sequences.
American Psychological Association (APA)
Zhu, Suguo& Du, Junping. 2014. Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-501445
Modern Language Association (MLA)
Zhu, Suguo& Du, Junping. Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy. Journal of Applied Mathematics No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-501445
American Medical Association (AMA)
Zhu, Suguo& Du, Junping. Visual Tracking Using Max-Average Pooling and Weight-Selection Strategy. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-501445
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-501445