Automatic detection method of human fall based on kinect skeleton tracking

Abstract

The invention provides an automatic human tumble detecting method based on Kinect skeleton tracking. The automatic human tumble detecting method includes tracking skeleton of a human body through Kinect, acquiring spatial coordinates of six skeleton joints including head, left shoulder, right shoulder, left hip, right hip and the center between hips (defined as human body centroid point), calculating motion speed of the human body centroid point and the distance between the human body centroid point and the ground surface, excluding non-tumble events, timing the stationary state of the human body centroid point to form six judgment conditions, judging whether human tumble events occur or not, and alarming through cellphone texts once tumble events occur. The automatic human tumble detecting method is low in misjudgment rate, and without wearable sensing devices and dependence on visible light, 24-hour continuous real-time detection of the human body can be realized.

Description

technical field [0001] The invention relates to an automatic detection method for human body fall based on Kinect skeleton tracking. Background technique [0002] The automatic detection method of human body fall refers to the technology of using external equipment to automatically monitor and detect daily activities in the human body detection environment to detect accidental human body fall events. At present, according to the technical principle of detecting fall events, the automatic human fall detection technology is mainly divided into three types: ① Based on wearable sensors: using three-axis accelerometers and three-axis gyroscopes to collect the acceleration values ​​of the trunk in various states and Angular velocity values, using the threshold method to detect fall events. However, the fall detection equipment based on wearable sensors is not comfortable to wear, hinders the normal movement of the human body, and has a high rate of false alarms and false negative...

AI Technical Summary

Problems solved by technology

However, it takes a lot of time to install and calibrate the camera lens; ordinary CCD cameras cannot work at night and under weak light conditions, and cannot perform continuous real-time detection; and it is easy to leak user privacy; The sound level and frequency level detect the occurrence of human fall incidents. This type of system has high requirements for the acoustic background of the detection environment, complex installation, large capital investment, and low accuracy.

In the existing literature, there have been automatic detection systems for human falls based on the above technologies, but their applicability and detection success rate in real life are not high

Images