Open AccessMasked Face Recognition
Author(s) -
Itrat Fatema,
Alfiya Khan,
Arti Gedekar,
Ayesha Khawaja,
Minakshi Barghat,
Nilofer Khan
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-1340
Subject(s) - facial recognition system , computer science , access control , face (sociological concept) , face masks , covid-19 , artificial intelligence , computer security , pattern recognition (psychology) , medicine , infectious disease (medical specialty) , social science , disease , sociology , pathology
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.