A multi-swarm particle swarm optimization algorithm for tracking multiple targets

Author

Hui Zheng ; Jing Jie ; Beiping Hou ; Zhengshun Fei

Author_Institution

Sch. of Autom. & Electr. Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China

fYear

2014

fDate

9-11 June 2014

Firstpage

1662

Lastpage

1665

Abstract

A novel multi-swarm particle swarm optimization algorithm to tracking multiple targets is proposed. The global swarm is divided into many sub-swarms according to the number of targets, and each sub-swarm searches for its target and maintains track of it. The information interaction between different sub-swarm is described as a differentiable energy function, which include an observation model and a mutual exclusion model. Experimental results demonstrate the efficiency of our method.

Keywords

computer vision; particle swarm optimisation; target tracking; computer vision; differentiable energy function; global swarm; information interaction; multiple targets tracking; multiswarm particle swarm optimization algorithm; mutual exclusion model; observation model; subswarms; Algorithm design and analysis; Histograms; Mathematical model; Optimization; Particle swarm optimization; Standards; Target tracking; Particle swarm optimization; energy minimization component; information interaction; multi-swarm;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4799-4316-6

Type

conf

DOI

10.1109/ICIEA.2014.6931434

Filename

6931434