In order to quickly and accurately detect the occurrence of falls in the elderly, this paper presents a real-time fall detection algorithm based on pose estimation. Firstly, the human pose estimation algorithm based on deep learning is used to obtain the coordinates of the joint point. Then, by calculating the falling speed of the centroid point when the human body falls, whether the ordinate value of the neck joint point after the fall is greater than the threshold, and the relative positional relationship of the shoulder-waist joint point in the image, whether the fall occurs is determined. The algorithm uses a monocular camera to detect, which is easily used in an embedded way for robots. The experimental results show that compared with the current advanced methods, the proposed algorithm has achieved good results.