Machine learning based human body temperature measurement and mask detection by thermal imaging

A. M., G. Udupa
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引用次数: 1

Abstract

The worldwide impact of the COVID-19 epidemic has been immense. Economic, educational, industrial, and other sectors all took a hit as a result of COVID-19. Unaware of how to address this, the health care industry was also hit. In the absence of a known cure, the most effective way to slow the spread of this fatal illness is to wear a face mask when doing so. Wearing a face mask when in public or conversing with people is also mandated by the WHO. Additionally, the most common symptom is high fever, which occurs in those who are unwell with this condition. As a result, we describe a system that can distinguish face masks using a regular RGB camera and identify persons with high body temperatures using a thermal camera with an 80x60 resolution. Tracking safety violations and encouraging the use of face masks may be achieved by using this method.
基于机器学习的人体体温测量和热成像面具检测
2019冠状病毒病疫情在全球造成巨大影响。经济、教育、工业和其他部门都受到了新冠肺炎的打击。由于不知道如何解决这个问题,医疗保健行业也受到了打击。在没有已知治疗方法的情况下,减缓这种致命疾病传播的最有效方法是在这样做时戴口罩。世卫组织还要求在公共场合或与人交谈时戴口罩。此外,最常见的症状是高烧,这发生在那些不舒服的人身上。因此,我们描述了一个系统,该系统可以使用普通RGB相机区分口罩,并使用80x60分辨率的热像仪识别高体温的人。通过使用这种方法,可以跟踪安全违规行为并鼓励使用口罩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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