A Visual Tracking Based on Particle Filter of Multi-algorithm Fusion

被引：0
作者：
Li, Tao [1 ]
Sun, Qiyuan [1 ,2 ]
机构：
[1] Tianjin Univ Technol, Sch Mech Engn, Tianjin 300384, Peoples R China
[2] Tianjin Key Lab Control Theory & Applicat Complic, Tianjin, Peoples R China
来源：
APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY | 2014年 / 513-517卷
关键词：
Visual tracking; Particle filter; Mean shift; Genetic algorithm; Resampling;
D O I：
10.4028/www.scientific.net/AMM.513-517.2893
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
A novel visual tracking algorithm based on particle filter with multi-algorithm fusion is proposed. Mean shift is employed to make particles distribute more reasonably in order to maintain tracking accuracy by using fewer particles, and the genetic evolution ideas is introduced to increase the diversity of samples by applying selection, crossover and mutation operator to achieve particles resampling. The experiments show that the tracking performance of the proposed method, compared with Mean Shift Embedded Particle Filter(MSEPF), is significantly improved.
引用
收藏
页码：2893 / 2896
页数：4
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