Abstract：In this paper, an adaptive particle filter for moving objects tracking is proposed. Mean shift is optimization algorithm based on gradient descended, which tracks moving targets through iterations. Particle filter is a robust method of tracking in non-Gauss and non-linear case. Firstly, a target model based on statistical histogram is proposed, which improves the classical histogram. Then Mean Shift algorithm and particle filter are integrated novelly through the statistical histogram target model. The parameters are modified according to the processing of tracking, so the effects caused by changed light or occlusion can be overcome. Experiments show that the method proposed by this paper can track moving target more powerful than Mean Shift tracked. Otherwise, even in complicated case, this method can still efficiently work.
2007, Vol. 29 
