Abnormal Crowd Detection in Public Places using OpenCV and Deep Learning

Abstract

Abstract: The rapid development of object detection algorithm as led to its widespread application in security, such as facial recognition and crowd surveillance. However, real-time tracking of an individual is very challenging, especially in crowded places where the person might be in part or entirely occluded for some period. Hence, this paper objective is to create abnormal activity detection in public places focusing only on people. This system does not just detect a person in real-time but in addition, uses the information it as learned to track the trajectory of the person until they exit the frame of the camera. The system uses the algorithm called YOLO for the person detection. The system was able to successfully detect the abnormal activity in public places and detect crowded group of people in live