基于Kinect V2的跌倒行为检测与分析

Detection and analysis on fall behavior based on Kinect V2

为了尽可能地降低老年人因跌倒而造成的伤亡,利用Kinect V2体感设备对老年人跌倒行为进行检测与识别,通过对Kinect摄像头获取的RGB-D图进行处理,得到人体骨骼图像和位置信息。利用骨架跟踪技术,选取人体中心点、两髋中心、右脚掌等骨骼点,实时计算人体中心点的空间位置、运动速度,以及两髋中心点的位置关系、离地面高度等参数。文中重点分析了跌倒时速度阈值和高度阈值。经过大量实验验证,在室内环境下,文中算法实时性高,能克服传统视频检测技术检测率低和实时性差的问题,在检测过程中能有效地保护老年人的隐私,不间断地实时检测,为老人意外跌倒提供安全保障。

The Kinect V2 somatosensory equipment is used to detect and identify the fall behavior of the elderly,so as to reduce the casualties caused by falls of the elderly as much as possible.The human body skeleton image and position information are obtained by processing the RGB-D images acquired by the Kinect camera.The skeleton tracking technology is used to select skeleton points such as the center point of the human body,center point of two hips,and right foot sole,so as to calculate the parameters such as the center point spatial position of the human body,body movement speed,position of the center point of two hips,and height of the center point of two hips from the ground in real time.The speed threshold and height threshold during the falling are emphatically analyzed in this paper.A large number of verification experiments were carried out.The results show that the algorithm proposed in this paper has a high real-time performance in the indoor environment,can overcome the problems of low detection rate and poor real-time performance of the traditional video detection technology,effectively protect the privacy of the elderly during the detection process,and perform real-time detection continuously,which can provide security assurance for accidental falls of the elderly.