A novel approach for fall detection in home environment

The system is specially developed for elderly people living alone in their homes. A novel method for detection of fall in home environment is presented. Video clips of certain duration specifying fall and non-fall activities are considered for experimentation. Shi-Tomasi algorithm is used to find interest points which are tracked by Pyramidal Lucas-Kanade algorithm. The speed and direction of motion is computed along with maximum displacement of interest point. Also the last positions of interest points were observed to declare the fall activity. The results show 95% accuracy for non-fall activities and 96.67% for fall activities with UR fall dataset.