关键词: 粒子滤波, 色彩直方图, 目标跟踪, 贝叶斯估计

Abstract: Particle Filter(PF) is an efficient tool for non-rigidity objects tracking. The paper presents a Bayesian-based PF method for objects tracking in dynamic scenes. Discussed the Bayesian estimation algorithm and the PF process. Used the color histograms correspond to the particles’ rectangles in the sequence images as the measurement and they are compared to the reference histogram so that to obtain the optimized posteriori probabilities. The robust mean technique is chosen to ascertain the objects’ positions. Single object and multi objects tracking are performed in the experiments. The results are compared with that of mean-shift algorithm. It’s proved that our method is more efficient.

Key words: Particle Filter, Color Histogram, Objects Tracking, Bayesian Estimation