Face Tracking Based on Adaptive PSO Particle Filter

This paper presents a new adaptive PSO particle filter face tracking algorithm.Our algorithm fully utilizes particle swarm optimization(PSO) ability to make the posterior probability distribution movements of the particle,meanwhile introduces the niche technology to improve the particle diversity,then the target distribution is nonlinear non-Gaussian and multi-mode,thus improves dynamic adaptive ability to the optimal solution of the dynamic system.Experimental results show that our algorithm has a good tracking accuracy and stability when comparing with particle filter and traditional PSO in the simple background,complex uniform and variable motion background.