Social Distancing and Face Mask Detection Using Deep Learning


Authors : K S Pavan Krishna; Harshita S; Nayan Deep; Gautham M G; Deepthi K

Volume/Issue : Volume 6 - 2021, Issue 6 - June

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3wpgpSF

The COVID-19 Pandemic caused by the new Coronavirus is the cause of this 21st-century global health crisis. It has forced the government to impose a lockdown to prevent the transmission of the virus. This led to the unprecedented shutdown of economic activities. The health care system is in crisis. Many different types of safety measures are being taken in order to reduce the risk of the spread of this disease at unprecedented times. Verified reports from renowned scientists and medial health practitioner indicated that wearing a face mask and maintaining social distance reduces the risk of transmitting the virus. Hence, we decided on an approach that is effective and economic by using deep learning techniques to create a safe environment in setups such as manufacturing plants, markets, malls, and other such places. To demonstrate our approach, the training dataset is composed of people, the images with and without the masks, which are collected from a variety of sources and use it in order to build a robust algorithm in order to measure the social distance with the help of the classic geometry methods. Our goal is to determine if a person is wearing a mask, or whether or not they maintain social distance as per protocols and guidelines which are given by leading scientists and governments in this pandemic. We hope that this study will serve as a useful tool for reducing the spread of this dangerous infectious disease in the world

Keywords : COVID-19, Face Mask Detection, Social Distancing, Deep Learning, CNN

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