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http://dx.doi.org/10.3837/tiis.2014.06.009

Efficient Mean-Shift Tracking Using an Improved Weighted Histogram Scheme  

Wang, Dejun (School of Computer Science and Technology Huazhong University of Science and Technology)
Chen, Kai (School of Computer Science and Technology Huazhong University of Science and Technology)
Sun, Weiping (School of Computer Science and Technology Huazhong University of Science and Technology)
Yu, Shengsheng (School of Computer Science and Technology Huazhong University of Science and Technology)
Wang, Hanbing (Wuhan Mechanical Technology College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.6, 2014 , pp. 1964-1981 More about this Journal
Abstract
An improved Mean-Shift (MS) tracker called joint CB-LBWH, which uses a combined weighted-histogram scheme of CBWH (Corrected Background-Weighted Histogram) and LBWH (likelihood-based Background-Weighted Histogram), is presented. Joint CB-LBWH is based on the notion that target representation employs both feature saliency and confidence to form a compound weighted histogram criterion. As the more prominent and confident features mean more significant for tracking the target, the tuned histogram by joint CB-LBWH can reduce the interference of background in target localization effectively. Comparative experimental results show that the proposed joint CB-LBWH scheme can significantly improve the efficiency and robustness of MS tracker when heavy occlusions and complex scenes exist.
Keywords
Target tracking; Mean-Shift; weighted histogram; target representation;
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