标题:An improved particle filter based on cuckoo search for visual tracking
作者:Gui-Xia, Fu ;Ming-Liang, Gao ;Guo-Feng, Zou ;Wen-Can, Liu ;Li-Na, Liu
作者机构:[Gui-Xia, Fu ;Ming-Liang, Gao ;Guo-Feng, Zou ;Li-Na, Liu ] School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo; 2 更多
会议名称:30th Chinese Control and Decision Conference, CCDC 2018
会议日期:June 9, 2018 - June 11, 2018
来源:Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
出版年:2018
页码:3687-3691
DOI:10.1109/CCDC.2018.8407763
摘要:Particle filter (PF) has been proven to be a powerful tool to solve visual tracking problem. However, the problem of sample impoverishment is a constraint of PF. To solve this problem, a cuckoo search-based particle filter is proposed. The particles in PF are optimized using cuckoo search. The meaningful particles are increased and can approximate the true state of the target more accurately. Experiments on visual tracking show that the proposed algorithm outperforms the standard particle filter in solve the visual tracking problems with various challenging conditions.
© 2018 IEEE.
收录类别:EI
资源类型:会议论文
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