Aiming at the problem that fall detection method of wearable device sensor

video analysis and environmental sensor has the disadvantages of limited storage resources

high computational resource consumption and low precision

a fall detection method in still image based on pose estimation is proposed. The method uses the convolutional neural network（ CNN） to extract the pose estimation of the human body

and judges whether the people is a fall state through the pose estimation of the human body

and uses the classification network to verify the fall posture. The experimental results show that the fall detection method in still image based on pose estimation has high recognition rate

low computational resource consumption and fast speed.