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所属单位：民航学院
发表刊物：Front. Comput. Sci.
摘要：In this paper, we propose a novel visual tracking method using a discriminative representation under a Bayesian framework. First, we exploit the histogram of gradient (HOG) to generate the texture features of the target templates and candidates. Second, we introduce a novel discriminative representation and ℓ2-regularized least squares method to solve the proposed representation model. The proposed model has a closed-form solution and very high computational efficiency. Third, a novel likelihood function and an update scheme considering the occlusion factor are adopted to improve the tracking performance of our proposed method. Both qualitative and quantitative evaluations on 15 challenging video sequences demonstrate that our method can achieve more robust tracking results in terms of the overlap rate and center location error. © 2019, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature.
ISSN号：2095-2228
是否译文：否
发表时间：2019-02-01
合写作者：Wang, Haijun
通讯作者：葛红娟