关键词: 相关滤波, 目标跟踪, 特征融合, 学习率自适应

Abstract: Aiming at the problem of image target tracking, in order to improve tracking accuracy, an adaptive correlation filter tracking algorithm based on multi feature fusion is proposed. The algorithm first selects two complementary features of HOG and CN, and trains two correlation filter trackers to track image targets respectively. Then, the response map weight of two trackers is calculated by using the reliability formula proposed in this paper and the decision is made by adaptive fusion. In the update stage of the filter, the algorithm adjusts the learning rate of the filter dynamically by combining the response graph confidence of the two features and the rate of change between the two frames. The simulation experiment uses 36 groups of color video sequences in the tracking datum database （OTB-2013） to test and compare the popular correlation filter tracking algorithm. The results show that the algorithm is better than the other algorithms in the average tracking accuracy, and has certain application value.

Key words: correlation filter, target tracking, feature fusion, adaptive learning rate