Title :
Particle Swarm Optimized Unscented Particle Filter for Target Tracking
Author :
Yang, Shuying ; Ma, Qin ; Huang, Wenjuan
Author_Institution :
Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China
Abstract :
In this paper, a novel particle swarm optimized (PSO) unscented particle filter (PSO-UPF) algorithm is proposed for target tracking. Unscented particle filter (UPF) can obtain the better sequential importance sampling than the traditional PF algorithm. Then we use PSO to optimize the state equation of UPF. So that the particle set can tend to the high likelihood region before the weights updated, thereby the impoverishment of particles can be overcome. While, the optimization process makes the particles which far away from the true state tend to the region where the true state has a greater probability of emergence, it can enhance the effect of each particle. Experiment results show that our modified particle filter algorithm uses fewer particles than the general particle filters and its performance outperforms them. And the accuracy of video tracking is improved.
Keywords :
importance sampling; particle filtering (numerical methods); particle swarm optimisation; probability; target tracking; PSO-UPF; particle swarm optimized-unscented particle filter algorithm; probability; sequential importance sampling; state equation; target tracking; Computer vision; Educational technology; Equations; Laboratories; Monte Carlo methods; Nonlinear dynamical systems; Particle filters; Particle swarm optimization; Signal processing algorithms; Target tracking;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5303440