利用人工智能监测社交距离以对抗COVID-19病毒传播

H. Alyami, Wael Alosaimi, M. Krichen, Roobaea Alroobaea
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引用次数: 3

摘要

为了控制COVID-19,公共卫生当局认为这是健康的距离,因此在公共场所人与人之间必须保持两米的距离。这样,“保持社交距离”的发生率与COVID-19的传播同步。为此,拟议的解决方案包括开发一种基于人工智能技术的工具,该工具将街道和公共空间的视频(实时)作为输入,并将不尊重社交距离的地方作为输出。检测到的不遵守社交距离的人用红色矩形包围,遵守社交距离的人用绿色矩形包围。这个解决方案已经在沙特阿拉伯麦加和麦地那两座神圣清真寺的视频案例中得到了测试。与文献中现有的方法相比,该解决方案是一项新颖的贡献,它允许检测不尊重社交距离的人的年龄、阶级和性别。人员检测使用带有ResNet-50的Faster RCNN进行,因为它是使用开源COCO数据集预训练的骨干网络。所获得的结果是令人满意的,并且可以通过考虑更复杂的相机、材料和技术来改进。
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Monitoring Social Distancing Using Artificial Intelligence for Fighting COVID-19 Virus Spread
To restrict COVID-19, individuals must remain two meters away from one another in public since public health authorities find this a healthy distance. In this way, the incidence of “social distancing” keeps pace with COVID-19 spread. For this purpose, the proposed solution consists of the development of a tool based on AI technologies which takes as input videos (in real time) from streets and public spaces and gives as output the places where social distancing is not respected. Detected persons who are not respecting social distancing are surrounded with red rectangles and those who respect social distancing with green rectangles. The solution has been tested for the case of videos from the two Holy Mosques in Saudi Arabia: Makkah and Madinah. As a novel contribution compared to existent approaches in the literature, the solution allows the detection of the age, class, and sex of persons not respecting social distancing. Person detection is performed using the Faster RCNN with ResNet-50 as it is the backbone network that is pre-trained with the open source COCO dataset. The obtained results are satisfactory and may be improved by considering more sophisticated cameras, material, and techniques.
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
16
期刊介绍: The International Journal of Open Source Software and Processes (IJOSSP) publishes high-quality peer-reviewed and original research articles on the large field of open source software and processes. This wide area entails many intriguing question and facets, including the special development process performed by a large number of geographically dispersed programmers, community issues like coordination and communication, motivations of the participants, and also economic and legal issues. Beyond this topic, open source software is an example of a highly distributed innovation process led by the users. Therefore, many aspects have relevance beyond the realm of software and its development. In this tradition, IJOSSP also publishes papers on these topics. IJOSSP is a multi-disciplinary outlet, and welcomes submissions from all relevant fields of research and applying a multitude of research approaches.
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