Abstract: In view of the imprecision of traditional tracking algorithms based on color histogram, a face tracking algorithm combining face multiple features based on adaptive fusion in the basic frame of particle filtering was presented.First, the color and edge features of the human face were extracted in the video sequence, while the weighted color histogram and edge orientation histogram(EOH) described facial features.Then, a self-adaptive features fusion strategy was employed to calculate particle set weight.The reliability of face tracking was enhanced by the self-adaptive features fusion strategy.Experimental results show that in the cases of complex backgrounds such as similar skin color, illumination change and so on, the proposed approach improves the tracking effect and has strong robustness.