Classical and modern face recognition approaches: a complete review
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Classical and modern face recognition approaches: a complete review Waqar Ali1,2 · Wenhong Tian3 · Salah Ud Din4 · Desire Iradukunda5 · Abdullah Aman Khan1 Received: 23 September 2019 / Revised: 10 July 2020 / Accepted: 9 September 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Human face recognition have been an active research area for the last few decades. Especially, during the last five years, it has gained significant research attention from multiple domains like computer vision, machine learning and artificial intelligence due to its remarkable progress and broad social applications. The primary goal of any face recognition system is to recognize the human identity from the static images, video data, data-streams and the knowledge of the context in which these data components are being actively used. In this review, we have highlighted major applications, challenges and trends of face recognition systems in social and scientific domains. The prime objective of this research is to sum-up recent face recognition techniques and develop a broad understanding of how these techniques behave on different datasets. Moreover, we discuss some key challenges such as variability in illumination, pose, aging, cosmetics, scale, occlusion, and background. Along with classical face recognition techniques, most recent research directions are deeply investigated, i.e., deep learning, sparse models and fuzzy set theory. Additionally, basic methodologies are briefly discussed, while contemporary research contributions are examined in broader details. Finally, this research presents future aspects of face recognition technologies and its potential significance in the upcoming digital society. Keywords Face recognition · Face identification · Artificial intelligence · Computer vision · Machine learning · Visual surveillance Waqar Ali
sirwaqar [email protected] 1
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2
Faculty of Information Technology, The University of Lahore, Lahore 54000, Pakistan
3
School of Information and Software Engineerng, University of Electronic Science and Technology of China, Chengdu 611731, China
4
Data Mining Lab, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
5
School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Multimedia Tools and Applications
1 Introduction Face as a human identity spans over the centuries in human civilizations. It has been one of the most proactively studied topics in computer vision and machine learning research for more than five decades. Compared with other common biometrics such as iris, retina or fingerprint based identification, face recognition has the ability to uncover uncooperative subjects in a proficient manner. In recent years, a lot of successful research outcomes have been recorded for images in a
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