The Search for the Best Real- Time Face Recognition Method for Finding Potential COVID Patients

Face detection and face recognition has been a part of our daily life for a while now. They usually help us speeding up the time of any identification process in many places. In early 2020, COVID-19 has become a worldwide pandemic and drives many people to find many solutions to this problem. Our contribution to the case is finding the best method to find potential COVID patients before they infect more people in public places by using facial detection and recognition. Using the PRISMA Flowchart methodology, which helps authors systematically analyze relevant publications and improve the quality of reports and meta-analyses The first matter to be solved is to find the most used algorithms used in facial detection and recognition, then followed by finding out which is the best one to be implemented for our case study. Our findings suggests that algorithms that can detect and recognize faces under occluded conditions works best for this case.