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Multiple object tracking (MOT) is an important technology in the field ofcomputer vision, which is widely used in automatic driving, intelligentmonitoring, behavior recognition and other directions. Among the currentpopular MOT methods based on deep learning, Detection Based Tracking (DBT) isthe most widely used in industry, and the performance of them depend on theirobject detection network. At present, the DBT algorithm with good performanceand the most widely used is YOLOv5-DeepSORT. Inspired by YOLOv5-DeepSORT, withthe proposal of YOLOv7 network, which performs better in object detection, weapply YOLOv7 as the object detection part to the DeepSORT, and proposeYOLOv7-DeepSORT. After experimental evaluation, compared with the previousYOLOv5-DeepSORT, YOLOv7-DeepSORT performances better in tracking accuracy.

Video object tracking based on YOLOv7 and DeepSORT