Posture-and-Fall-Detection-System-Using-3D-Motion-Sensors:这项工作提出了一种监督学习方法,用于训练姿势检测分类器,并使用Microsoft Kinect v2传感器使用姿势分类结果作为输入来实施跌倒检测系统。 Kinect v2骨架跟踪为25个身体部位提供3D深度坐标。 我们使用这些深度坐标来提取七个特征,这些特征包括对象的高度和某些身体部位之间的六个角度。 然后将这些特征输入到完全连接的神经网络中,该神经网络输出对象的三种已考虑姿势之一-源码

上传者: 42099814 | 上传时间: 2021-09-24 15:17:28 | 文件大小: 18.11MB | 文件类型: ZIP
使用3D运动传感器的姿势和跌倒检测系统 这项工作提出了一种监督学习方法,用于训练姿势检测分类器,并使用Microsoft Kinect v2传感器使用姿势分类结果作为输入来实施跌倒检测系统。 Kinect v2骨架跟踪为25个身体部位提供3D深度坐标。 我们使用这些深度坐标来提取七个特征,这些特征包括对象的高度和某些身体部位之间的六个角度。 然后将这些特征输入到完全连接的神经网络中,该神经网络输出对象的三种已考虑姿势之一:站立,坐着或躺下。 在由多个对象组成的测试数据上,所有三种姿势的平均分类率均达到99.30%以上,这些对象大部分时间甚至没有面对Kinect深度相机,并且位于不同的位置。 这些结果表明,采用提议的设置对人体姿势进行分类的可行性与对象在房间中的位置以及3D传感器的方向无关。 系统演示请观看Posture_fall_detection_demo.mp4视频,以了解姿势和跌倒

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