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Title: Visual tracking via temporally smooth sparse coding
Authors: Liu, Ting
Wang, Gang
Wang, Li
Chan, Kap Luk
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2014
Source: Liu, T., Wang, G., Wang, L., & Chan, K. L. (2015). Visual tracking via temporally smooth sparse coding. IEEE signal processing letters, 22(9), 1452-1456.
Series/Report no.: IEEE signal processing letters
Abstract: Sparse 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.
DOI: 10.1109/LSP.2014.2365363
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:].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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