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

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 re...

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Published in东华大学学报(英文版) Vol. 33; no. 5; pp. 745 - 748
Main Author 韩华 王裕明 张玉金 胡一帆
Format Journal Article
LanguageEnglish
Published School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China%School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China 31.10.2016
Shandong Computer Science Center(National Supercomputer Center in Jinan), Jinan 250014, China
Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai 201203, China%Shandong Provincial Key Laboratory of Computer Network, Jinan 250014, China
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ISSN1672-5220

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Abstract 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.
AbstractList 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.
Author 韩华 王裕明 张玉金 胡一帆
AuthorAffiliation School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai 201203, China Shandong Provincial Key Laboratory of Computer Network, Jinan 250014, China Shandong Computer Science Center (National Supercomputer Center in Jinan ) , Jinan 250014, China
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Keywords residual resampling
stratified resampling
systematic resampling
video target tracking
multinomial resampling
Language English
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Tracking running shortcomings realization overcome stratified shortest smallest steps overlapping
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.
HAN Hua1, WANG Yu-ming1, ZHANG Yu-jin1,2, HU Yi-fa3,4( 1 School of Electron& 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)
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Shandong Computer Science Center(National Supercomputer Center in Jinan), Jinan 250014, China
Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai 201203, China%Shandong Provincial Key Laboratory of Computer Network, Jinan 250014, China
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Title Performance of Resampling Algorithms Based on Particle Filter in Video Target Tracking
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