Three-States-Transition Method for Fall Detection Algorithm Using Depth Image
Three-States-Transition Method for Fall Detection Algorithm Using Depth Image
复制标题
使用深度图像的跌倒检测算法的三态转移方法
DOI：
10.20965/jrm.2019.p0088
复制
发表时间：
2019
期刊：
影响因子：
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通讯作者：
Hiroyuki Tomiyama
中科院分区：
文献类型：
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作者：
Xiangbo Kong;Zelin Meng;Lin Meng;Hiroyuki Tomiyama
目前，世界各地老年人的比例正在增加，涉及跌倒的事故已成为一个严重的问题，特别是对于那些独居的人。在本文中，提出了一种增强算法，以检测老年人客厅中的此类跌倒。我们之前的算法是利用深度相机获得二值图像，然后通过Canny边缘检测得到二值图像的轮廓。然后，该算法计算每个轮廓像素的切矢量角度，并将其划分为15°范围组。如果大部分切线角度低于45°，则检测到坠落。传统的跌落检测系统无法检测到对着摄像机的跌落，因此在相关工作中至少需要两台摄像机。为了检测向相机方向的跌倒，本研究提出了一种三状态转换方法来区分跌倒状态和坐下状态。该算法计算不同的位置状态，并将这些状态分为三组来检测人的当前状态。此外，为了区分静止状态和下落状态，计算了过渡速度。本研究构建了一个包含1500多幅图像的数据集，对图像的实验评估表明，我们的增强算法仅用单个相机就可以有效地检测到瀑布。
Currently, the proportion of elderly persons is increasing all over the world, and accidents involving falls have become a serious problem especially for those who live alone. In this paper, an enhancement to our algorithm to detect such falls in an elderly person’s living room is proposed. Our previous algorithm obtains a binary image by using a depth camera and obtains an outline of the binary image by Canny edge detection. This algorithm then calculates the tangent vector angles of each outline pixels and divide them into 15° range groups. If most of the tangent angles are below 45°, a fall is detected. Traditional fall detection systems cannot detect falls towards the camera so at least two cameras are necessary in related works. To detect falls towards the camera, this study proposes the addition of a three-states-transition method to distinguish a fall state from a sitting-down one. The proposed algorithm computes the different position states and divides these states into three groups to detect the person’s current state. Futhermore, transition speed is calculated in order to differentiate sit states from fall states. This study constructes a data set that includes over 1500 images, and the experimental evaluation of the images demonstrates that our enhanced algorithm is effective for detecting the falls with only a single camera.