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ACCV
2010
Springer

Efficient Visual Object Tracking with Online Nearest Neighbor Classifier

11 years 1 months ago
Efficient Visual Object Tracking with Online Nearest Neighbor Classifier
Abstract. A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection and pruning method to achieve stability and plasticity in tracking targets of changing appearance. Experiments show that near-frame-rate performance is achieved (sans feature detection), and that the state of the art is improved in terms of handling occlusions, clutter, changes of scale, and of appearance. A theoretical analysis shows why nearest neighbor works better than more sophisticated classifiers in the context of tracking.
Steve Gu, Ying Zheng, Carlo Tomasi
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2010
Where ACCV
Authors Steve Gu, Ying Zheng, Carlo Tomasi
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