A method for judging fall behavior of solitary elderly people based on motion tracking

With the arrival of the aging society, more and more empty nest elderly appear. In order to solve the security problems caused by the fall of the empty nest elderly, this paper proposes a method to judge the elderly's fall based on motion tracking. The method combines LBP features and chromaticity features to detect the moving target. Then, the Kalman filter and Camshift were used to track the detected target. Based on the tracking results, a judgment strategy was put forward. The experimental results show that this method has a high accuracy in judging the behavior of the elderly.