A Coarse-to-Fine Searching Method with Kernel Matching Based on Bhattacharyya Coefficients
LI Liang-Fu1,2,3, FENG Zu-Ren2, CHEN Wei-Dong1 , ZHENG Bao-Zhong1
1.The No.205 Institute of China Ordnance Industry Corporation Group, Xi'an 7100652. System Engineering Institute, Xi'an Jiaotong University, Xi'an 7100493. College of Computer Science, Shaanxi Normal University, Xi'an 710062
Abstract：Mean shift is an efficient pattern match algorithm. Aiming at object tracking in large motion area, a mean shift algorithm is proposed based on coarse-to-fine searching with kernel matching. It can efficiently use a similarity measure function to realize the rough location of motion object. Then, the mean shift method is used to obtain the accurate local optimal value by iterative computing, and thus object tracking in large motion area is successfully realized. Experimental results show it has good performance in accuracy and speed compared with traditional algorithm.
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2008, Vol. 21 
