Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems

Author(s): B.S. Maya*, T. Asha, P. Prajwal, P.N. Revanth, Pratik R Pailwan and Rahul Kumar Gupta

DOI: 10.2174/9781681089553122010008

Safe Distance and Face Mask Detection using OpenCV and MobileNetV2

Pp: 76-95 (20)

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Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

Abstract

The COVID-19 epidemic affects humans irrespective of race, religion, standing, and caste. It has affected more than 20 million people worldwide. Wearing face masks and taking public safety measures are two advanced safety measures that need to be taken in open areas to prevent the spread of the disease. To create a secure environment that contributes to public safety, we propose a computer-based method that focuses on automatic real-time surveillance to identify safe general distance and face masks in public places using a model to monitor movement and detect camera violations. We achieve 97.6% specificity with the help of OpenCV and MobileNetV2 strategies.

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