Hierarchical particle filter tracking algorithm based on multi-feature fusion

作     者：Minggang Gan Yulong Cheng Yanan Wang Jie Chen 

作者机构：School of AutomationBeijing Institute of Technology 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2016年第27卷第1期

页      面：51-62页

核心收录：

学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China(61304097) the Projects of Major International(Regional)Joint Research Program NSFC(61120106010) the Foundation for Innovation Research Groups of the National National Natural Science Foundation of China(61321002) 

主　　题：particle filter corner matching multi feature fusion local binary patterns(LBP) backstepping. 

摘      要：A hierarchical particle filter（HPF） framework based on multi-feature fusion is *** proposed HPF effectively uses different feature information to avoid the tracking failure based on the single feature in a complicated *** this approach,the Harris algorithm is introduced to detect the corner points of the object,and the corner matching algorithm based on singular value decomposition is used to compute the firstorder weights and make particles centralize in the high likelihood *** the local binary pattern（LBP） operator is used to build the observation model of the target based on the color and texture features,by which the second-order weights of particles and the accurate location of the target can be ***,a backstepping controller is proposed to complete the whole tracking *** and experiments are carried out,and the results show that the HPF algorithm with the backstepping controller achieves stable and accurate tracking with good robustness in complex environments.