A Survey of Research on Crowd Abnormal Behavior Detection Algorithm Based on YOLO Network

Abstract

Thanks to the rapid development of computer vision technology, methods based on in-depth learning have gradually replaced counting methods based on traditional machine learning, and substantial progress has been made in the accuracy and real-time detection of abnormal crowd behavior detection. Firstly, it introduces the structure and application of the YOLO network of the one-stage detection system. Secondly, according to the development of the YOLO network model, it specifically introduces the abnormal behavior detection algorithms and research based on the YOLO v3 network, the YOLOv4 network and the YOLO v5 network. Finally, the summary The shortcomings of the current One-stage target detection network are analyzed, and the future research directions are prospected.