In order to solve the problem that traditional target tracking cannot be accurately tracked after occlusion, a target tracking algorithm combining YOLO and Camshift algorithm is proposed. Building a model of target detection using YOLO network structure, before the model is constructed, the image frame is preprocessed by image enhancement method, while maintaining sufficient image information in the video frame, improving the image quality and reducing the time complexity of the YOLO algorithm. The target is determined by the YOLO algorithm, and the initialization of the target tracking is completed. According to the position information of the target, the Camshift algorithm is used to process the subsequent video frames, and the target of each frame is updated, so that the position of the search window can be continuously adjusted to adapt to the movement of the target. The experimental results show that the proposed method can effectively overcome the problem of tracking loss after the target is occluded, and has good robustness.