DocumentCode :
1719304
Title :
Meanshift algorithm based on kernel bandwidth adaptive adjust
Author :
Yunji Zhao ; Hailong Pei ; Baoluo Liu
Author_Institution :
Sch. of Electr. Eng. & Autom., Henan Polytech. Univ., Jiaozuo, China
fYear :
2013
Firstpage :
4486
Lastpage :
4490
Abstract :
Object tracking algorithm based on Meanshift algorithm with fixed kernel bandwidth does not realize object tracking correctly with the scale of object changed. According to this, a scheme of kernel bandwidth adaptive adjustment and predictions of object cancroids based on Kalman filter is proposed in this paper. In this algorithm, Object location predicted based on Kalman filter is used to initialize the Meanshift algorithm. The variation tendency of the kernel bandwidth is also determined based on Kalman filter. Experiment results demonstrate that this algorithm can realize the kernel bandwidth adaptive adjustment and object location prediction. The robustness of the tracking algorithm is also enhanced.
Keywords :
Kalman filters; object tracking; Kalman filter; fixed-kernel bandwidth adaptive adjustment; kernel bandwidth variation tendency; meanshift algorithm initialization; object cancroid predictions; object location prediction; object tracking algorithm robustness enhancement; Bandwidth; Conferences; Electronic mail; Kalman filters; Kernel; Prediction algorithms; Robustness; Kalman Filter; Kernel Bandwidth; Meanshift Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
Type :
conf
Filename :
6640210
Link To Document :
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