Document Type

Journal Article

Department/Unit

Department of Computer Science

Title

Single object tracking via robust combination of particle filter and sparse representation

Language

English

Abstract

© 2014 Elsevier B.V.The drifting problem is a core problem in single object tracking and attracts many researchers' attention. Unfortunately, traditional methods cannot well solve the drifting problem. In this paper, we propose a tracking method based on the robust combination of particle filter and reverse sparse representation (RC-PFRSR) to reduce the drifting. First, we find the ill-organized coefficients. Second, we propose a diagonal matrix α, whose diagonal line includes each patch contribution factor, to function each patch coefficient value of one candidate obtained by sparse representation. Third, we adaptively discriminate the power of each patch within the current candidate region by an occlusion prediction scheme. Our experimental results on nine challenging video sequences show that our RC-PFRSR method is effective and outperforms six state-of-the-art methods for single object tracking.

Keywords

Occlusion prediction, Particle filter, Sparse representation, Template update, Visual object tracking

Publication Date

2015

Source Publication Title

Signal Processing

Volume

110

Start Page

178

End Page

187

Publisher

Elsevier

DOI

10.1016/j.sigpro.2014.09.020

ISSN (print)

01651684

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