Abstract
Face recognition plays an important role in the field of biometrics. Detecting a face from a video or an image is a very popular topic in biometric research. The wide applications of face recognition in the real world are security systems, video surveillance, interaction of human and computer, and many more. Many algorithms have been developed so far and its proficiency has been on the forefront of research from the past two decades. This paper attempts to review the methods like PCA, LDA, CNN, SVM for face detection and on the various hybrid combinations of these techniques to deal with the challenges of face recognition. In addition, illuminations, pose variations, aging, and facial expressions have been discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abdullah NA, Jamri Saidi Md., Ab Rahman NH, Wen CC, Hamid IRA (2017) Face recognition for criminal identification: an implementation of principal component analysis for face recognition. In: AIP conference proceedings 1891, 020002
Bah SM, Ming. An improved face recognition algorithm and its application in attendance management system
Kakade SD (2016) A review paper on face recognition techniques. 2(2). ISSN : 2494-9150
Ahmad F, Najam A, Ahmed Z. Image-based face detection and recognition
Gan J, Zhou D, Li C (2005) A method for improved PCA in face recognition. Int J Inform Technol 11(11)
Singh S, Prasad SVAV (2018) Techniques and challenges of face recognition: a critical review. In: 8th international conference on advances in computing and communication (ICACC-2018)
Gorkberg B, Salah AA, Riccio D, Dugelay J-L. 3D face recognition
Lu J, Plataniotis KN, Venetsanopoulos AN (2003) Face recognition using LDA-based algorithms. IEEE Trans. Neural Networks 14(1) (2003)
Vinay A, Shekhar VS, Balasubramanya Murthy KN, Natarajan S. Face recognition using gabor wavelet features with PCA and KPCA—a comparative study
Parkhi OM, Vedaldi A, Zisserman A. Deep face recognition
Coşkun M, Uçar A, Yıldırım Ö, Demir Y. Face recognition based on convolutional neural network
Pradhan A (2012) Support vector machine—a survey. Int J Emerging Technol Adv Eng 2(8). ISSN 2250–2459
Li SZ, Jain AK. Handbook of face recognition
Singh R, Vatsa M, Noore A, Singh SK. Age transformation for improving face recognition performance
Zhanga T, Fanga B, Yuanb Y, Tanga YY, Shanga Z, Lia D, Langa F. Multiscale facial structure representation for face recognition under varying illumination
Jabid T, Hasanul Kabir Md., Chae O. Local directional pattern (L DP) for face recognition
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Azmeen, J., Borah, D.J. (2021). Face Recognition Techniques, Challenges: A Review. In: Marriwala, N., Tripathi, C.C., Jain, S., Mathapathi, S. (eds) Soft Computing for Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1048-6_27
Download citation
DOI: https://doi.org/10.1007/978-981-16-1048-6_27
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-1047-9
Online ISBN: 978-981-16-1048-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)