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Learning structured visual dictionary for object tracking
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DOI：10.1016/j.imavis.2013.09.008.png)
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摘要
En 中文
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. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Object tracking
Bag of features
Appearance model
Geometric relationship
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