title: Sequential Monte Carlo-guided ensemble tracking.
abstract: A great deal of robustness is allowed when visual tracking is considered as a classification problem. This paper combines a finite number of weak classifiers in a SMC framework as a strong classifier. The time-varying ensemble parameters (confidence of weak classifiers) are regarded as sequential arriving states and their posterior distribution is estimated in a Bayesian manner. Therefore, both the adaptiveness and stability are kept for the ensemble classification in handling scene changes and target deformation. Moreover, to increase the tracking accuracy, weak classifiers including Support Vector Machine (SVM) and Large Margin Distribution Machine (LDM) are combined as a hybrid strong one, with adaptiveness to the sample scales. Comprehensive experiments are performed on benchmark videos with various tracking challenges, and the proposed method is demonstrated to be better than or comparable to the state-of-the-art trackers.
authors.affiliation: Computer Science and Information Technology, North-East Normal University, Changchun, Jilin Province, China.
authors.forename: Yuru
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Computer Science and Information Technology, North-East Normal University, Changchun, Jilin Province, China.
authors.forename: Qiaoyuan
authors.identifier: http://orcid.org/0000-0001-8921-1493
authors.initials: Q
authors.lastname: Liu
authors.affiliation: School of Information Engineering, Jilin Business and Technology College, Changchun, Jilin Province, China.
authors.forename: Longkui
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Computer Science and Information Technology, North-East Normal University, Changchun, Jilin Province, China.
authors.forename: Minghao
authors.initials: M
authors.lastname: Yin
authors.affiliation: Jilin University, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun, Jilin Province, China.
authors.forename: Shengsheng
authors.initials: S
authors.lastname: Wang
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003670:Deer; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009010:Monte Carlo Method; D009038:Motion; D060388:Support Vector Machine; D014741:Video Recording