Physical Distancing Detection using YOLO v3 and Bird's Eye View Transform
Physical Distancing Detection using YOLO v3 and Bird's Eye View Transform
复制标题
使用 YOLO v3 和鸟瞰图变换进行物理距离检测
DOI：
10.1109/icitech50181.2021.9590157
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Iwan Setyawan
中科院分区：
文献类型：
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作者：
Jane Chrestella Marutotamtama;Iwan Setyawan
大多数国家的政府为遏制Covid-19的传播而制定的一项规定是保持身体距离。然而，许多人仍然忽视了这一规定的重要性。因此，开发一个能够帮助执行这一规定的系统是很重要的。在本文中，我们提出了一个可以自动检测视频帧中人类的存在并测量他们彼此之间距离的系统。使用YOLO v3进行目标检测，使用鸟瞰变换增强距离测量的精度。我们的实验表明，与没有进行转换的系统相比，使用这种转换产生的精度提高高达20.93%（即从74.42%提高到95,35%）。
One regulation that has been established by governments in most countries to curb the spread of Covid-19 is physical distancing. However, many people still ignore the importance of this regulation. Thus, it is important to develop a system that can help enforcing this regulation. In this paper, we propose a system that can automatically detect the presence of humans in a video frame and measure their distances from each other. Object detection is performed using YOLO v3 and the accuracy of distance measurement is enhanced using Bird's Eye View Transformation. Our experiments show that using this transformation yields an accuracy improvement of up to 20.93% compared to the performance of the system without transformation (i.e., from 74.42% to 95, 35% accuracy).