In this paper, we present the human fall detection, which is the important part of automatic monitoring of the activities of daily living. The proposed method is divided into 3 steps: motion detection and tracking based on background subtraction with shadow removal; human features extraction: aspect ratio , fall angle and these acceleration; fall detection: extracted features are used for fall detection analysis. Experimental results show that our system can detect falls quite accurately and discriminate a fall from normal activities
