Online Learning Discriminative Dictionary with Label Information for Robust Object Tracking
Joint Authors
Fan, Baojie
Du, Yingkui
Cong, Yang
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A supervised approach to online-learn a structured sparse and discriminative representation for object tracking is presented.
Label information from training data is incorporated into the dictionary learning process to construct a robust and discriminative dictionary.
This is accomplished by adding an ideal-code regularization term and classification error term to the total objective function.
By minimizing the total objective function, we learn the high quality dictionary and optimal linear multiclassifier jointly using iterative reweighed least squares algorithm.
Combined with robust sparse coding, the learned classifier is employed directly to separate the object from background.
As the tracking continues, the proposed algorithm alternates between robust sparse coding and dictionary updating.
Experimental evaluations on the challenging sequences show that the proposed algorithm performs favorably against state-of-the-art methods in terms of effectiveness, accuracy, and robustness.
American Psychological Association (APA)
Fan, Baojie& Du, Yingkui& Cong, Yang. 2014. Online Learning Discriminative Dictionary with Label Information for Robust Object Tracking. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1013447
Modern Language Association (MLA)
Fan, Baojie…[et al.]. Online Learning Discriminative Dictionary with Label Information for Robust Object Tracking. Abstract and Applied Analysis No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1013447
American Medical Association (AMA)
Fan, Baojie& Du, Yingkui& Cong, Yang. Online Learning Discriminative Dictionary with Label Information for Robust Object Tracking. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1013447
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1013447