Affiliation:
1. Anjuman College of Engineering and Technology, Nagpur, Maharashtra, India
Abstract
The World is facing a huge health crisis due to the rapid transmission of coronavirus (COVID-19). In order to effectively prevent the spread of COVID-19 virus, almost everyone have to wear a mask as its one of the most important element to prevent from this virus as per World Health Organization (WHO). It makes conventional facial recognition technology almost ineffective in several cases, such as community access control, face access control, facial attendance, facial security checks at airports, etc. Thus, there's an immediate requirement to improve the recognition performance of the existing technology on the masked faces. The current advanced face recognition approaches are architected based on deep learning, which depend on or requires a large number of face samples. With no publicly accessible datasets or database of face samples available, a dataset needs to be created for the recognition system.
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