Abstract
Comparing with the advantages and disadvantages of the existing target tracking algorithms based on deep learning, a vehicle tracking algorithm based on Yolov2 and GOTURN algorithm is proposed, which is called YOLOv2-tracker vehicle tracking algorithm. The Algorithm is trained and tested by using the collected training set and test set. The results show that the YOLOv2-tracker vehicle tracking algorithm can achieve higher tracking accuracy and faster tracking speed, and can effectively overcome environmental interference. Further analysis of the test results, the algorithm found that there is “errof” phenomenon, the paper discusses and analyzes the causes of this phenomenon, and put forward a reasonable solution. In addition, a “dynamic save” method is proposed to solve the “lost track” problem.
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