识别未戴口罩的面孔:在公共场所防范COVID-19和其他感染

G. Aggarwal, Atharv Sinha, Pranav Srivastava, Prerna Agarwal
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摘要

冠状病毒的浪潮正在席卷全球。医生和科学家们也处于研制疫苗的最后阶段。但是,由于生产、供应链、冷链和价格等几个因素,使每个人都获得疫苗是具有挑战性的。在此之前,防止感染的唯一方法是佩戴标记并保持社交距离。本文介绍了如何利用图像处理算法在公共场所识别有面具和无面具的人脸。世界各地人们为保持安全而采取的重要措施之一是戴口罩。这个基于研究的项目得到了一个基于摄像头的解决方案来检测和识别数据库中存在的人脸。如果直播流有未屏蔽的面孔,而这些面孔不存在于现有数据库中,则发出警报以提醒管理员或用户。在这样的时代,这是一个重要的项目,因为现在,随着全球因金融危机而结束的封锁,大多数公共场所,如商场、寺庙、商店、杂货店和药店都在开放。对我们周围每个人的安全和福祉的担忧,因为病毒可以以对数速度传播,并以大额钞票的形式造成大规模损害,在某些情况下还会造成死亡。为了避免这种情况,我们在公共场所总是要戴口罩,这就是这个项目所做的。在我们的手稿中使用的关键技术是人脸检测,人脸识别与识别,人脸特征检测。
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Identification of Unmasked Faces: Protection in Public Places from COVID-19 and Other Infections
The $3^{\mathrm{r}\mathrm{d}}$ wave of Coronavirus is hitting the world. The doctors and scientists are also in their last phase of developing a vaccine. But it is challenging to get the vaccine for everyone due to several factors such as production, supply chain, cold chain and price. Till then, the only way to prevent infection is to wear a mark and follow social distancing. This paper describes how to identify mask and no-mask faces in public areas using image processing algorithms. One of the significant steps taken by people around the world to stay safe is wearing masks. This research-based project gets a camera-based solution to detect faces and recognize them if they exist in the database. If the live stream has unmasked faces, which aren’t present in the existing database, give out an alarm to alert the administrator or user. It is a significant project for times like these because now, with the lockdown ending in the world because of financial meltdowns, most public places like malls, temples, shops, grocery stores, and medical stores are opening. A concern for the safety and well-being of everyone around us because the virus can spread at a logarithmic rate and cause mass damage in the form of large bills and some cases, death. To avoid this, we always have to wear masks when in public places, and this is what the project does. The crucial technologies used in our manuscript are Face Detection, Face Recognition & Identification, and Feature Detection in the face.
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