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With the development of deep learning and artificial intelligence technology, video object tracking has become an important research content of computer vision. Video object tracking plays a more and more important role in public security, human-computer interaction, traffic control, military and other fields. Although a variety of object tracking algorithms have been proposed by scholars, and a relatively perfect object tracking system has also been built, the robustness of the algorithm is still a big challenge. In this paper, the structure of moving object tracking system is briefly introduced. At the same time, the main moving object tracking algorithms are described in detail from feature extraction and fusion, appearance model, object search and so on. Then, a new development of object tracking algorithm in deep learning environment is analyzed. From the perspective of object tracking and object detection algorithm based on deep learning, the effectiveness of deep learning in improving the robustness of object detection algorithm is analyzed. Finally, the specific application of video object detection algorithm is summarized and its future development is prospected.