Human Anomaly Detection using Deep Learning

Abstract

Human Anomaly Detection can be used in order to identify thefts, terrorist attacks, fighting, and fires in susceptible areas including banks, parking areas, hospitals, shopping malls, universities, colleges, schools, borders, airports, bus and railway stations, etc. Video surveillance can be used in crowded areas to identify anomalies and analyse human behaviour to detect theft and vandalism. It will also help to prevent inappropriate behaviour such as fighting among humans by monitoring the perimeter of the location, for the safety of people. It can be used to monitor the suspicious activity of humans in crowded places.