Research Article
Open access
Published on 31 July 2024
Download pdf
Wang,S. (2024). Facial recognition - A literature review. Applied and Computational Engineering,87,6-13.
Export citation

Facial recognition - A literature review

Shengdi Wang *,1,
  • 1 University of Sheffield

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/87/20241560

Abstract

This paper analyses the main technologies for face recognition, a critical biometric tool for identity verification and security across various sectors. A comprehensive overview of traditional and modern facial recognition technologies will be provided, examining their key features such as age, pose, and illumination. The study discusses the evolution and current state of facial recognition, highlighting significant advancements and applications in recent years. The objective is to offer a detailed understanding of how these technologies function and their implications for security and identity verification.

Keywords

face recognition, biometrics, neural networks, applications.

[1]. Zhao, W., Chellappa, R., Phillips, P. J., & Rosenfeld, A. (2003). Face recognition: A literature survey. ACM computing surveys (CSUR), 35(4), 399-458.

[2]. Adini, Y., Moses, Y., & Ullman, S. (1997). Face recognition: The problem of compensating for changes in illumination direction. IEEE Transactions on pattern analysis and machine intelligence, 19(7), 721-732.

[3]. Jain, A. K., & Li, S. Z. (2011). Handbook of face recognition (Vol. 1, p. 699). New York: springer.

[4]. Kaur, P., Krishan, K., Sharma, S. K., & Kanchan, T. (2020). Facial-recognition algorithms: A literature review. Medicine, Science and the Law, 60(2), 131-139.

[5]. Zhou, S. K., & Chellappa, R. (2005). Image-based face recognition under illumination and pose variations. JOSA A, 22(2), 217-229.

[6]. Partridge, D., & Griffith, N. (2002). Multiple classifier systems: Software engineered, automatically modular leading to a taxonomic overview. Pattern Analysis & Applications, 5, 180-188.

[7]. Lanitis, A., Taylor, C. J., & Cootes, T. F. (2002). Toward automatic simulation of ageing effects on face images. IEEE Transactions on pattern Analysis and machine Intelligence, 24(4), 442-455.

[8]. Ellavarason, E., Guest, R., Deravi, F., Sanchez-Riello, R., & Corsetti, B. (2020). Touch-dynamics based behavioural biometrics on mobile devices–a review from a usability and performance perspective. ACM Computing Surveys (CSUR), 53(6), 1-36.

[9]. Kshirsagar, V. P., Baviskar, M. R., & Gaikwad, M. E. (2011, March). Face recognition using Eigenfaces. In 2011 3rd International Conference on Computer Research and Development (Vol. 2, pp. 302-306). IEEE.

[10]. Turk, M., & Pentland, A. (1991). Eigenfaces for recognition. Journal of cognitive neuroscience, 3(1), 71-86.

[11]. Gao, Y., & Leung, M.K. (2002). Face Recognition Using Line Edge Map. IEEE Trans. Pattern Anal. Mach. Intell., 24, 764-779.

[12]. Yongsheng Gao and M. K. H. Leung, "Face recognition using line edge map," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 764-779, June 2002.

[13]. Taigman, Y., Yang, M., Ranzato, M. A., & Wolf, L. (2014). Deepface: Closing the gap to human-level performance in face verification. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1701-1708).

[14]. Ratcliffe, J. (2006). Video surveillance of public places. Washington, DC: US Department of Justice, Office of Community Oriented Policing Services.

Cite this article

Wang,S. (2024). Facial recognition - A literature review. Applied and Computational Engineering,87,6-13.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 6th International Conference on Computing and Data Science

Conference website: https://www.confcds.org/
ISBN:978-1-83558-585-6(Print) / 978-1-83558-586-3(Online)
Conference date: 12 September 2024
Editor:Alan Wang, Roman Bauer
Series: Applied and Computational Engineering
Volume number: Vol.87
ISSN:2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).