Correlation filtering target tracking method based on self-adaptive weight combined learning

The invention discloses a correlation filtering target tracking method based on self-adaptive weight combined learning and belongs to the field of machine vision. According to the method, a correlation filtering model and a color model based on a color histogram are combined, the discrimination characteristics of the correlation filtering model are fully utilized to effectively distinguish a target and a background, and meanwhile histogram scores are acquired through the color model to better cope with occlusion, blockage, deformation and other complicated environments. In order to fully utilize the advantages of the two models, confidence weights are proposed to self-adaptively combine the two models. Meanwhile, when a correlation filter is trained, background information is fully utilized to construct spatial regularization items, interference of the background information is effectively suppressed, and the robustness of an algorithm in the tracking process is further improved. For the purpose of making a t