Facial Recognition Databases: Recent Developments and Review of Methods

Abstract

Facial recognition is one of the most important biometrics that many researchers are increasingly studying, as it is used in various applications such as surveillance, security, law enforcement, information, person identification, smart cards, access control, etc. There is a fundamental relationship between the development of facial recognition algorithms and the possibility of the existence of databases of different faces that influence the appearance of the face in a constrained manner. Standard datasets of images of appropriate size for a subject should be accessible to the public to compare the performance and assessment of identification or verification of a facial recognition system. This paper aims to present a review of the most popular 2D unmasked and masked face datasets available in the current century that are accessible for free download or can be certified with an acceptable effort, where these databases are suitable for training and testing 2D face recognition approaches. Also, this review discussed the evaluation metrics for face recognition and their two types of tasks (identification and verification).