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| Double-Ring Mean Shift Algorithm for Visual Tracking |
| XIA Yu1,2,WU Xiao-Jun1,WANG Hong-Yuan3 |
1.School of IoT Engineering,Jiangnan University,Wuxi 214122
2.Changshu College,Jiangsu Radio TV University,Changshu 215500
3.School of Information Science Engineering,Changzhou University,Changzhou 213164 |
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Abstract A tracking algorithm based on double-ring Mean Shift is proposed to solve the deficiency of target representation,template similarity measure and fixed kernel-bandwidth in traditional Mean Shift tracking algorithm. The feature extraction model based on universal elliptical region is used to reduce the influence of background feature and improve the quality of target model effectively. Double-ring descriptor is presented to emphasize the importance of target feature and improve the peak modality of matching function. The proposed method updates the bandwidth of kernel-function adaptively by the relationship of double-ring. The experimental results show that the proposed tracking approach is robust and invariant to scale,pose and partial occlusions.
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Received: 12 April 2012
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2013, Vol. 26 
