Kinect depth image-based human body fall detection method and device

A technology of depth image and detection method, applied in image enhancement, image analysis, image data processing and other directions, can solve the problems of high false alarm rate and large amount of calculation, and achieve the effect of high accuracy and small amount of calculation

Active Publication Date: 2017-09-22
NANCHANG UNIV
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Problems solved by technology

[0005] In view of the above situation, it is necessary to provide a human body fall detection method and device based on Kinect depth

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  • Kinect depth image-based human body fall detection method and device
  • Kinect depth image-based human body fall detection method and device
  • Kinect depth image-based human body fall detection method and device

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[0065] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, in which the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the drawings are exemplary, and are only used to explain the present invention, but should not be understood as limiting the present invention.

[0066] These and other aspects of the embodiments of the present invention will become clear with reference to the following description and drawings. In these descriptions and drawings, some specific implementations in the embodiments of the present invention are specifically disclosed to show some ways of implementing the principles of the embodiments of the present invention, but it should be understood that the scope of the embodiments of the present invention is not This restriction. On the contrary, the e...

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Abstract

The invention discloses a Kinect depth image-based human body fall detection method and device. The method comprises the following steps of: analyzing each frame of depth image of a video shot by a Kinect camera, and determining a bone center point, a shoulder joint center point and a waist center point of a human body in the current depth image; calculating an included angle formed by an upper body trunk center line and a gravity line of the human body in the current depth image so as to obtain the current gravity angle of the human body, wherein the upper body trunk center line is a connection line between the bone center point and the shoulder joint center point of the human body; when the current gravity angle is greater than a threshold angle, calculating a change rate of the gravity angle and a change rate of a centroid height at each time point, wherein the centroid height is a distance between the waist center point and a reference surface or a reference point; and when the change rate of the gravity angle at any time point is greater than a first preset value and the change rate of the centroid height is greater than a second preset value, determining that the human body falls.

Description

technical field [0001] The invention relates to the field of human body fall detection, in particular to a human body fall detection method and device based on a Kinect depth image. Background technique [0002] The detection method of human body fall is widely used in the monitoring of the elderly and children in the family and the monitoring of patients in the hospital. It mainly automatically monitors the activities of the human body through external equipment to detect accidental human fall events. Quickly and effectively discovering the fall behavior can enable the faller to get help in time, shorten the waiting time for help, and minimize the risk of falling. [0003] The existing fall detection core algorithms can be divided into three categories: one is to monitor the height of the center of mass of the detected person through the wearable device, and judge the fall with the real-time monitoring data returned by the wearable device; the other is to use the environmen...

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Application Information

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IPC IPC(8): G06T7/60G06T7/66
CPCG06T7/60G06T2207/10028G06T2207/30196G06T7/66
Inventor 姚磊岳闵卫东
Owner NANCHANG UNIV
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