Fall detection for elderly persons using a depth camera
Xiangbo Kong, Lin Meng, Hiroyuki Tomiyama · 2017
Currently, the proportion of elderly persons is increasing all over the world, and the fall accident has become a serious problem for elderly persons, especially the elderly person who lives alone. In this paper, we proposed an algorithm for detecting dangerous situations in the living room for protecting elderly persons. In this study, we get the binary image by using depth camera, and get the outline of the binary image by canny filter. Then we detect the fall by using the output outline image. We get all the white pixels in the outline image, then we calculate the tangent vector angle of each white pixels and divide them into 15° groups. If most tangent angles are below 45°, the fall is detected. The database includes over 700 images and the experimental evaluation of experimental images demonstrates that the proposed algorithm is an effective method for detecting the fall.