In order to deal with complex scene change problem in the tracking process, we propose a tracking algorithm via multiple feature fusion. Under the framework of particle filter, dynamic feature weights are calculated by making an uncertain measure of each feature in the tracking process, which results in adaptive feature fusion. The algorithm uses the complementarity of color, space and texture features to improve the tracking performance. Experimental results show that the algorithm can adapt to complex scene changes such as scale, rotation and motion blur. Compared with traditional algorithms, the proposed algorithm has obvious advantages to complete the tracking task.