Joint object region location and deep feature learning for fall recognition

Chaobo Li, Hongjun Li, Yupeng Ding, Ke Xu, Wenmin Zhang

Abstract: Fall recognition plays an important role in the life of the elderly. In this paper, a method of jointing object region location and deep feature learning for fall recognition is proposed. Firstly, we collect and analyze the color images and the depth images. Secondly, automatic location for object region on collected images is performed. Thirdly, deep feature learning based on the convolution neural network is used to extract deep features and to detect fall. The experimental results show that the proposed algorithm is robust and the recognition rate is higher than some corresponding methods.