关键词: 目标跟踪, 视觉显著性, 颜色直方图, 加速鲁棒特征（SURF）, 粒子滤波, KLT算法

Abstract: In order to track moving targets of video exactly, a novel tracking scheme is proposed using particle filter based on improved color histogram features and Speeded Up Robust Features（SURF）. SURF algorithm is applied to extracting features. The features are tracked stably by the hierarchically iterative matching of the Kanade-Lucas-Tomasi（KLT） matching algorithm. Based on?fusion mode of multiplicative weights, the SURF and improved saliency weighted color histogram are used to the joint observation probability. Meanwhile, for avoiding the drop of SURF matching numbers and the instability in tracking process, a SURF feature-point-set update method is presented. Through using multi-group experiments, the results demonstrate that this approach has great robustness for either sunlight or block and has high accuracy in tracking.

Key words: target tracking, visual saliency, color histogram, Speeded Up Robust Features（SURF）, particle filter, KLT algorithm