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.
