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Performance of Resampling Algorithms Based on Particle Filter in Video Target Tracking
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作者 韩华 王裕明 +1 位作者 张玉金 胡一帆 《Journal of Donghua University(English Edition)》 EI CAS 2016年第5期745-748,共4页
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... 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. 展开更多
关键词 tracking running shortcomings realization overcome stratified shortest smallest steps overlapping
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