Performance of Resampling Algorithms Based on Particle Filter in Video Target Tracking  

作　　者：韩华 王裕明 张玉金 胡一帆 

机构地区：[1]School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China [2]Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai 201203, China [3]Shandong Provincial Key Laboratory of Computer Network, Jinan 250014, China [4]Shandong Computer Science Center (National Supercomputer Center in Jinan ) , Jinan 250014, China

出　　处：《Journal of Donghua University(English Edition)》2016年第5期745-748,共4页东华大学学报（英文版）

基　　金：National Natural Science Foundations of China(Nos.61272097,61305014,61401257);China Scholarship Council(No.201508310033);Innovation Program of Shanghai Municipal Education Commission,China(No.14ZZ156);Natural Science Foundation of Shanghai,China(No.13ZR1455200);"Chen Guang"Project Supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation,China(No.13CG60);Funding Scheme for Training Young Teachers in Shanghai Colleges,China(No.ZZGJD13006);The Connotative Construction Projects of Shanghai Local Colleges in the 12th Five-Year,China(Nos.nhky-201442,nhrc-2015-11);The Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security,China(No.AGK2015006)

摘　　要：Particle filter is a common algorithm in video target tracking.But there are still some shortcomings,for example,particle degradation phenomenon.For solving this problem,the general solution is to introduce resampling step.At present,four kinds of resampling algorithms are widely used:multinomial resampling,residual resampling,stratified resampling and systematic resampling algorithms.In this paper,the performances of these four resampling algorithms were analyzed from realization principle,uniform distribution theory and computational complexity.Finally,through a series of video target tracking experiments,the systematic resampling algorithm had the smallest calculation load,the shortest running time and the maximum number of effective particles.So,it can be concluded that in the field of video target tracking,the systematic resampling algorithm has more advantages than other three algorithms both in the running time and the number of effective particles.Particle filter is a common algorithm in video target tracking.But there are still some shortcomings,for example,particle degradation phenomenon.For solving this problem,the general solution is to introduce resampling step.At present,four kinds of resampling algorithms are widely used：multinomial resampling,residual resampling,stratified resampling and systematic resampling algorithms.In this paper,the performances of these four resampling algorithms were analyzed from realization principle,uniform distribution theory and computational complexity.Finally,through a series of video target tracking experiments,the systematic resampling algorithm had the smallest calculation load,the shortest running time and the maximum number of effective particles.So,it can be concluded that in the field of video target tracking,the systematic resampling algorithm has more advantages than other three algorithms both in the running time and the number of effective particles.

关 键 词：Tracking running shortcomings realization overcome stratified shortest smallest steps overlapping 

分 类 号：TP14[自动化与计算机技术—控制理论与控制工程]