Open AccessA Comprehensive Study on Occlusion Invariant Face Recognition under Face Mask Occlusions
Author(s) -
Susith Hemathilaka,
Achala Aponso
Publication year - 2021
Publication title -
machine learning and applications
Language(s) - English
Resource type - Journals
ISSN - 2394-0840
DOI - 10.5121/mlaij.2021.8401
Subject(s) - artificial intelligence , facial recognition system , computer science , face (sociological concept) , computer vision , occlusion , face masks , low resolution , three dimensional face recognition , face hallucination , invariant (physics) , covid-19 , pattern recognition (psychology) , face detection , high resolution , mathematics , medicine , geography , social science , remote sensing , disease , pathology , sociology , infectious disease (medical specialty) , cardiology , mathematical physics
The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face, and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features.