Human Posture Recognition and fall detection Using Kinect V2 Camera

Abstract

Based on the depth information and skeleton tracking technology of Microsoft Kinectv2 sensor, this paper performs human body gesture recognition and realizes human fall detection based on this. First, the depth of the Kinect V2 sensor is used to process the human joints produced by the skeleton tracker. Then the optimized BP neural network is used for posture recognition, and the fall is detected on this basis. The neural network is trained using the dataset generated by the Kinect tracker,but use a different body tracker (NITE) for testing. Finally, the posture recognition and fall detection were experimentally verified. We performed real-time testing (up to 3.5 meters) over the entire working range of the sensor. Through experiments, the overall accuracy of the NITE tracker for fall testing was 98.5%, and the worst accuracy was 97.3%.