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Robust Online Object Tracking Based on Feature Grouping and 2DPCA
Joint Authors
Jiang, Ming-Xin
Zhang, Jun-Xing
Li, Min
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-10
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA).
Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases.
Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames.
Then, the projection matrix is learned according to the more discriminative image and the less discriminative image, and the samples are projected.
The object tracking results are obtained using Bayesian maximum a posteriori probability estimation.
Finally, we employ a template update strategy which combines incremental subspace learning and the error matrix to reduce tracking drift.
Compared with other popular methods, our method reduces the computational complexity and is very robust to abnormal changes.
Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm achieves more favorable performance than several state-of-the-art methods.
American Psychological Association (APA)
Jiang, Ming-Xin& Zhang, Jun-Xing& Li, Min. 2013. Robust Online Object Tracking Based on Feature Grouping and 2DPCA. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1009099
Modern Language Association (MLA)
Jiang, Ming-Xin…[et al.]. Robust Online Object Tracking Based on Feature Grouping and 2DPCA. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1009099
American Medical Association (AMA)
Jiang, Ming-Xin& Zhang, Jun-Xing& Li, Min. Robust Online Object Tracking Based on Feature Grouping and 2DPCA. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1009099
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009099