Video based automatic fall detection in indoor environment

An increase in population of elderly people living in isolated environments, leads to the need for an automated monitoring system. Fall is one of the major reasons for death of elderly people. So fall detection is an essential part of an automated indoor monitoring system. Video based automatic fall detection is robust and more reliable than other fall detection methods. Most of the available video based fall detection mechanisms are based on the extraction of motion dynamic features like velocity and intensity gradient of the person in video. These methods are computationally intensive and less accurate. This paper presents an accurate and computationally less intensive approach to detect fall, using only the static features of the person such as aspect ratio and inclination angle. Experimental results show that this method is robust in detecting all kinds of fall.