Learning structured visual dictionary for object tracking

Fan Yang; Huchuan Lu; Ming Hsuan Yang

doi:10.1016/j.imavis.2013.09.008

Learning structured visual dictionary for object tracking

Fan Yang, Huchuan Lu, Ming Hsuan Yang

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

In this paper, we propose a visual tracking algorithm by incorporating the appearance information gathered from two collaborative feature sets and exploiting its geometric structures. A structured visual dictionary (SVD) can be learned from both appearance and geometric structure, thereby enhancing its discriminative strength between the foreground object and the background. Experimental results show that the proposed tracking algorithm using SVD (SVDTrack) performs favorably against the state-of-the-art methods.

Original language	English
Pages (from-to)	992-999
Number of pages	8
Journal	Image and Vision Computing
Volume	31
Issue number	12
DOIs	https://doi.org/10.1016/j.imavis.2013.09.008
Publication status	Published - 2013

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Vision and Pattern Recognition

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10.1016/j.imavis.2013.09.008

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