[1]杨张振.基于Kinect 的摔倒行为研究[J].计算机技术与发展,2018,28(04):179-182.[doi:10.3969/ j. issn.1673-629X.2018.04.038]
　YANG Zhang-zhen.Research on Fall Detection Based on Kinect[J].,2018,28(04):179-182.[doi:10.3969/ j. issn.1673-629X.2018.04.038]
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基于Kinect 的摔倒行为研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年04期
页码:
179-182
栏目:
应用开发研究
出版日期:
2018-04-10

文章信息/Info

Title:
Research on Fall Detection Based on Kinect
文章编号:
1673-629X(2018)04-0179-04
作者:
杨张振
南京邮电大学 通信与信息工程学院,江苏 南京 210003
Author(s):
YANG Zhang-zhen
School of Telecommunications &Information Engineering,Nanjing University of
Posts and Telecommunications,Nanjing 210003,China
关键词:
Kinect; 深度图像; 骨骼图像; 摔倒; 向量
Keywords:
Kinect; depth image; skeleton image; fall; vector
分类号:
TP39
DOI:
10.3969/ j. issn.1673-629X.2018.04.038
文献标志码:
A
摘要:
针对传统视频检测技术识别效率低和实时性差的问题,提出基于 Kinect 体感设备对人体摔倒行为进行判断识别。其中人体位于 Kinect 的检测范围之内,通过对 Kinect 设备获取到的深度图像进行处理,得到人体骨骼图像及人体关节点的位置信息；利用 Kinect 骨骼追踪技术,参考人体左肩、右肩 2 个骨骼点,以两肩中心点为目标,实时计算两肩中心关节点的空间位置、相对位置等参数,计算出不同帧之间两肩中心点位置之间的位移变化,并结合该位移向量与 O - X,Y,Z 坐标体系中的 Y 轴方向夹角,以二者相结合为条件来判断人体是否出现摔倒事件。 经过实验验证,在室内环境中,该方法能够实现人体摔倒的自动实时检测,并且利用深度信息和骨骼信息对摔倒行为进行检测判断,能够有效地保护监测环境内当事人的个人隐私。
Abstract:
Aiming at the problem of low efficiency and poor real-time performance of traditional video detection technology,we propose to judge and identify the human body，s fall based on Kinect somatosensory equipment. In this paper,the human body is located within the detection range of Kinect,and the location information of human skeleton images and human joint can be acquired by the processing of depth images from the Kinect. Referred to the two bone points on the left and right shoulder,with the center of them as the object,we calculate the parameters like spatial position,relative position in the center node of two shoulders in real-time by Kinect bone tracking technology and displacement variation between the center points of the two shoulders out of different frames. Combined the angle between the displacement vector and the axis Y in the coordinate system of O - X,Y,Z and the displacement variation as the conditions,it is necessary to judge whether the human body has a fall event. Experiments show that in the indoor environment,the proposed method can realize the automatic real-time detection of the human body，s fall,and uses the depth information and the skeletal information to judge the fall behavior,which can effectively protect the personal privacy of the parties in the monitoring environment.

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更新日期/Last Update: 2018-06-08