In order to satisfy the requirements of visual tracking algorithm on tracking accuracy and speed, a multi-scale correlation filtering visual tracking algorithm combined with target detection is proposed. The proposed algorithm is first used to find the target location and size in the image by the target detection algorithm based on depth learning. The correlation filtering algorithm is then applied to the visual tracking of the given target features and the multi-scale search of the optimal response. When the correlation filtering response appears abnormal, the model stops updating. When the response value of several frames continues to be abnormal, the search of target location and size is then made in the whole image. By the evaluation of tracking states and the adaptive adjustment of model updating rate, the proposed algorithm solves the problem of tracking error accumulation over time in the traditional correlation filter algorithm, and possesses high tracking speed and high precision. The results show that as for the proposed algorithm on the Matlab platform, the average positioning precision is 0.593, the average overlap precision is 0.784, and the frame rate is 65.3 frame/s.