Traditional particle filter tracking algorithm is difficult to get accurate target location in the complicated circumstance. In order to solve these problems, a novel particle filter tracking algorithm based on online feature selection is proposed. Firstly, the algorithm converted the input image into sixteen different color feature spaces, and fisher discriminating rule was adopted to select the top-ranked feature space which could discriminate the target region and the neighbor background region best. Then, particle filter algorithm based on statistical histogram was applied to track object in the top-ranked feature space. Experimental results show that this algorithm is robust and the target is tracked accurately under the conditions of illumination variation, shape change of target and partial occlusion.