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Open AccessReview

Face Recognition Systems: A Survey

1
AI-ED Department, Yncrea Ouest, 20 rue du Cuirassé de Bretagne, 29200 Brest, France
2
Electronic and Micro-electronic Laboratory, Faculty of Sciences of Monastir, University of Monastir, Monastir 5000, Tunisia
3
College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(2), 342; https://doi.org/10.3390/s20020342
Received: 15 October 2019 / Revised: 12 December 2019 / Accepted: 15 December 2019 / Published: 7 January 2020
(This article belongs to the Special Issue Biometric Systems)
Over the past few decades, interest in theories and algorithms for face recognition has been growing rapidly. Video surveillance, criminal identification, building access control, and unmanned and autonomous vehicles are just a few examples of concrete applications that are gaining attraction among industries. Various techniques are being developed including local, holistic, and hybrid approaches, which provide a face image description using only a few face image features or the whole facial features. The main contribution of this survey is to review some well-known techniques for each approach and to give the taxonomy of their categories. In the paper, a detailed comparison between these techniques is exposed by listing the advantages and the disadvantages of their schemes in terms of robustness, accuracy, complexity, and discrimination. One interesting feature mentioned in the paper is about the database used for face recognition. An overview of the most commonly used databases, including those of supervised and unsupervised learning, is given. Numerical results of the most interesting techniques are given along with the context of experiments and challenges handled by these techniques. Finally, a solid discussion is given in the paper about future directions in terms of techniques to be used for face recognition. View Full-Text
Keywords: face recognition systems; person identification; biometric systems; survey face recognition systems; person identification; biometric systems; survey
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Kortli, Y.; Jridi, M.; Al Falou, A.; Atri, M. Face Recognition Systems: A Survey. Sensors 2020, 20, 342.

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