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dc.contributor.authorLiu, Tingen
dc.contributor.authorWang, Gangen
dc.contributor.authorWang, Lien
dc.contributor.authorChan, Kap Luken
dc.identifier.citationLiu, T., Wang, G., Wang, L., & Chan, K. L. (2015). Visual tracking via temporally smooth sparse coding. IEEE signal processing letters, 22(9), 1452-1456.en
dc.description.abstractSparse representation has been popular in visual tracking recently for its robustness and accuracy. However, for most conventional sparse coding based trackers, the target candidates are considered independently between consecutive frames. This paper shows that the temporal correlation of these frames can be exploited to improve the performance of tracking and makes the tracker more robust to noise. Furthermore, to improve the tracking speed, we revisit a more efficient method for `1 norm problem, marginal regression, which can solve the sparse coding problem more efficiently. Consequently we can realize real-time tracking based on the temporal smooth sparse representation. Extensive experiments have been done to demonstrate the effectiveness and efficiency of our method.en
dc.format.extent5 p.en
dc.relation.ispartofseriesIEEE signal processing lettersen
dc.rights© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [Article DOI:].en
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen
dc.titleVisual tracking via temporally smooth sparse codingen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.description.versionAccepted versionen
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