Classical and modern face recognition approaches: a complete review

• Published in: Multimedia tools and applications Vol. 80; no. 3; pp. 4825 - 4880
• Main Authors: Ali, Waqar, Tian, Wenhong, Din, Salah Ud, Iradukunda, Desire, Khan, Abdullah Aman
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2021; Springer Nature B.V
• Subjects: Artificial intelligence; Computer Communication Networks; Computer Science; Computer vision; Cosmetics; Data Structures and Information Theory; Data transmission; Domains; Face recognition; Fuzzy set theory; Fuzzy sets; Machine learning; Multimedia Information Systems; Object recognition; Occlusion; Special Purpose and Application-Based Systems; Video data; Computer vision; Visual surveillance; Face recognition; Face identification; Artificial intelligence; Machine learning
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-020-09850-1

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.