A Multiple Object Tracking Algorithm Based on YOLO Detection

In order to further improve the accuracy and the efficiency of multi-target tracking, a multi-target tracking algorithm based on YOLO is proposed. Firstly, the video stream is detected by YOLO algorithm for multi-target detection. After obtaining the target size, position and other information, the depth feature extraction is performed, the noise data of the unrelated regions in the image is removed, and the complexity of calculation and time of feature extraction are reduced. LSTM (long short-term memory) obtains the temporal relationship between frames and frames. Finally, the Euclidean distance is used to measure the similarity so as to achieve target matching and association and complete the tracking of multiple targets in the video stream. Experiments on the open target tracking data set MOT-16 and MSR Data Set show that the proposed algorithm is workable on multi-target tracking.