NEWS

COMPARATIVE STUDY OF MACHINE LEARNING AND DEEP LEARNING ALGORITHM FOR FACE RECOGNITION


(Received: 28-Jun.-2021, Revised: 17-Aug.-2021 , Accepted: 19-Aug.-2021)
In the present world, biometric systems are used to analyze and verify a person's distinctive bodily or behavioral features for authentication or recognition. Till now, there are numerous authentication systems that use iris, fingerprint and face feature for identification and verification, where the face recognition-based systems are most widely preferred, as they do not require user help every time, are more automated and are easy to function. This review paper provides a comparative study between various face recognition techniques and their hybrid combinations. The most commonly used datasets in this domain are also analyzed and reviewed. We have also highlighted the future scope and challenges in this domain, as well as various Deep Learning (DL)-based algorithms for facial recognition.

[1] Z. Mortezaie and H. Hassanpour, "A Survey on Age-invariant Face Recognition Methods," Jordanian Journal of Computers and Information Technology (JJCIT), vol. 05, no. 02, pp. 87-96, August 2019.

[2] W. LU and M. YANG, "Face Detection Based on Viola-Jones Algorithm Applying Composite Features," Proc. of the IEEE Int. Conf. on Robots & Intell. Sys. (ICRIS), pp. 82-85, Haikou, China, 2019.

[3] H. Li, Z. Lin, X. Shen, J. Brandt and G. Hua, "A Convolutional Neural Network Cascade for Face Detection," Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 5325- 5334, DOI: 10.1109/CVPR.2015.7299170, Boston, USA, 2015.

[4] H. Chen, Y. Chen, X. Tian and R. Jiang, "A Cascade Face Spoofing Detector Based on Face Anti- spoofing R-CNN and Improved Retinex LBP," IEEE Access, vol. 7, pp. 170116-170133, 2019.

[5] X. Hu and B. Huang, "Face Detection Based on SSD and CamShift," Proc. of the IEEE 9th Joint Int. Inform. Techn. and Artificial Intelligence Conf. (ITAIC), pp. 2324-2328, Chongqing, China, 2020.

[6] F. Wang, F. Xie, S. Shen, L. Huang, R. Sun and J. Le Yang, "A Novel Multi Face Recognition Method with Short Training Time and Lightweight Based on ABASNet and H-Softmax," IEEE Access, vol. 8, pp. 175370-175384, DOI: 10.1109/ACCESS.2020.3026421, 2020.

[7] F. S. Samaria and A. C. Harter, "Parameterization of a Stochastic Model for Human Face Identification," Proc. of IEEE Workshop on Applications of Computer Vision, 1994, pp. 138-142, Sarasota, USA, 1994.

[8] M. Wang, L. Song, K. Sun and Z. Jia, "F-2D-QPCA: A Quaternion Principal Component Analysis Method for Color Face Recognition," IEEE Access, vol. 8, pp. 217437-217446, 2020.

[9] J. Kong, M. Chen, M. Jiang, J. Sun and J. Hou, "Face Recognition Based on CSGF(2D)2PCANet," IEEE Access, vol. 6, pp. 45153-45165, DOI: 10.1109/ACCESS.2018.2865425, 2018.

[10] A. Martinez and R. Benavente, "The AR Face Database," CVC Technical Report 24, [Online], Available: http://www2.ece.ohio-state.edu/~aleix/ARdatabase.html, 1998. 

[11] C. Low, A. B. Teoh and C. Ng, "Multi-fold Gabor, PCA and ICA Filter Convolution Descriptor for Face Recognition," IEEE Trans. on Circuits and Systems for Video Techn., vol. 29, no. 1, pp. 115-129, 2019.

[12] Y. Zhang, X. Xiao, L. Yang, Y. Xiang and S. Zhong, "Secure and Efficient Outsourcing of PCA-based Face Recognition," IEEE Trans. on Information Forensics and Security, vol. 15, pp. 1683-1695, 2020.

[13] C. Y. Low, A. B. J. Teoh and K. A. Toh, "Stacking PCA Net+: An Overly Simplified Conv Nets Baseline for Face Recognition," IEEE Signal Processing Letters, vol. 24, no. 11, 2017.

[14] A.S. Georghiades, P.N. Belhumeur and D.J. Kriegman, "From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 6, pp. 643–660, 2021.

[15] P. J. Phillips, H. Wechsler, J. Huang and P. J. Rauss, "The FERET Database and Evaluation Procedure for Face-recognition Algorithms," Image and Vision Computing, vol. 16, no. 5, pp. 295-306, 1998.

[16] The Georgia Tech Face Database, [Online], Available: http://www.anefian.com/research/face_reco.htm.

[17] K. Messer, J. Matas, J. Kittler, J. Luettin and G. Maitre, "XM2VTSDB: The Extended M2VTS Database," Proc. of the 2nd International Conference on Audio and Video-based Biometric Person Authentication, vol. 964, pp. 965-966, 2000.

[18] G. B. Huang, M. Mattar, T. Berg and E. Learned-Miller, "Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments," Proc. of Workshop on Faces in ‘Real-Life’ Images: Detection, Alignment and Recognition, [Onlive], Available: https://hal.inria.fr/inria-00321923, Marseille, France, 2008.

[19] L. Wolf, T. Hassner and I. Maoz, "Face Recognition in Unconstrained Videos with Matched Background Similarity," Proc. of CVPR 2011, pp. 529-534, DOI: 10.1109/CVPR.2011.5995566, Colorado Springs, USA, 2011.

[20] S. Dalali and L. Suresh, "Daubechives Wavelet Based Face Recognition Using Modified LBP," Procedia Computer Science, vol. 93, pp. 344-350, 2016, DOI:10.1016/j.procs.2016.07.219, 2016.

[21] J. Tang, Q. Su, B. Su, S. Fong, W. Cao and X. Gong, "Parallel Ensemble Learning of Convolutional Neural Networks and Local Binary Patterns for Face Recognition," Computer Methods and Programs in Biomedicine, vol. 197, DOI: 10.1016/j.cmpb.2020.105622, 2020.

[22] M. A. Muqeet and R. S. Holambe, "Local Binary Patterns Based on Directional Wavelet Transform for Expression and Pose-invariant Face Recognition," Applied Computing and Informatics, vol. 15, no.2, pp. 163-171, DOI: 10.1016/j.aci.2017.11.002, 2019.

[23] C. E. Thomaz and G. A. Giraldi, "A New Ranking Method for Principal Component Analysis and Its Application to Face Image Analysis," Image and Vision Computing, vol. 28, no. 6, pp. 902-913, DOI: 10.1016/j.imavis.2009.11.005, 2010.

[24] W. Zhang and S. Xiang, "Face Anti-spoofing Detection Based on DWT-LBP-DCT Features," Signal Processing: Image Communication, vol. 89, Paper ID: 115990, DOI: 10.1016/j.image.2020.115990, 2020.

[25] L. Shi, X. Wang and Y. Shen, "Research on 3D Face Recognition Method Based on LBP and SVM," Optik, vol. 220, Paper ID: 165157, DOI: 10.1016/j.ijleo.2020.165157, 2020.

[26] I. Chingovska, A. Anjos and S. Marcel, "On the Effectiveness of Local Binary Patterns in Face Anti- Spoofing," Proceedings of the IEEE International Conference of Biometrics Special Interest Group (BIOSIG), pp. 1-7, Darmstadt, Germany, 2012.

[27] Z. Zhang, J. Yan, S. Liu, Z. Lei, D. Yi and S. Z. Li, "A Face Anti Spoofing Database with Diverse Attacks," Proc. of the 5th IAPR IEEE International Conference on Biometrics (ICB), pp. 26-31, DOI: 10.1109/ICB.2012.6199754, New Delhi, India, 2012.

[28] J. Žemgulys, V. Raudonis, R. Maskeliūnas and R. Damaševičius, "Recognition of Basketball Referee Signals from Videos Using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM)," Procedia Computer Science, vol. 130, pp. 953-960, 2018.

[29] R. Rameswari, S. N. Kumar, M. A. Aananth and C. Deepak, "Automated Access Control System Using Face Recognition," Materials Today: Proceedings, vol. 45, DOI: 10.1016/j.matpr.2020.04.664, 2020.

[30] A. Chitlangia and G. Malathi, "Handwriting Analysis Based on Histogram of Oriented Gradient for Predicting Personality Traits Using SVM," Procedia Computer Science, vol. 165, pp. 384-390, DOI: 10.1016/j.procs.2020.0, 2019. 

[31] D. Lakshmi and R. Ponnusamy, "Facial Emotion Recognition Using Modified HOG and LBP Features with Deep Stacked Autoencoders," Microprocessors and Microsystems, vol. 82, DOI: 10.1016/j.micpro.2021.103834, 2021.

[32] M. Lyons, M.Kamachi and J. Gyoba, "The Japanese Female Facial Expression (JAFFE) Database," The Japanese Female Facial Expression (JAFFE) Dataset, Zenodo, DOI: 10.5281/zenodo.3451524, 1998.

[33] P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar and I. Matthews, "The Extended Cohn-Kanade Dataset (CK+): A Complete Dataset for Action Unit and Emotion-specified Expression," Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, pp. 94- 101, DOI: 10.1109/CVPRW.2010.5543262, San Francisco, USA, 2010.

[34] G. Yan, M. Yu, Y. Yu and L. Fan, "Real-time Vehicle Detection Using Histograms of Oriented Gradients and AdaBoost Classification," Optik, vol. 127, no. 19, pp. 7941-7951, 2016.

[35] J. Arróspide, L. Salgado and M. Nieto, "Video Analysis Based Vehicle Detection and Tracking Using an MCMC Sampling Framework," EURASIP Journal on Advances in Signal Processing, vol. 2012, Article ID: 2012 (2), DOI: 10.1186/1687-6180-2012-2, 2012.

[36] Y.-D. Zhang, Z.-J. Yang, H.-M. Lu, X.-X. Zhou, P. Philips, Q.-M. Liu and S.-H. Wang, "Facial Emotion Recognition Based on Biorthogonal Wavelet Entropy, Fuzzy Support Vector Machine and Stratified Cross Validation," IEEE Access, vol. 4, pp. 8375-8385, DOI: 10.1109/ACCESS.2016.2628407, 2016.

[37] T. T. D. Pham and C. S. Won, "Facial Action Units for Training Convolutional Neural Networks," IEEE Access, vol. 7, pp. 77816-77824, DOI: 10.1109/ACCESS.2019.2921241, 2019.

[38] I. Omara, A. Hagag, S. Chaib, G. Ma, F. E. Abd El-Samie and E. Song, "A Hybrid Model Combining Learning Distance Metric and DAG Support Vector Machine for Multimodal Biometric Recognition," IEEE Access, vol. 9, pp. 4784-4796, DOI: 10.1109/ACCESS.2020.3035110, 2021.

[39] F. Zhang and F. Wang, "Exercise Fatigue Detection Algorithm Based on Video Image Information Extraction," IEEE Access, vol. 8, pp. 199696-199709, DOI: 10.1109/ACCESS.2020.3023648, 2020.

[40] A. R. Syafeeza, M. Khalil-Hani, S. S. Liew and R. Bakhteri, "Convolutional Neural Network for Face Recognition with Pose and Illumination Variation," International Journal of Engineering and Technology (IJET), vol. 6, no. 1, pp. 44-57, 2014.

[41] E. Zangeneh, M. Rahmati and Y. Mohsenzadeh, "Low Resolution Face Recognition Using a Two-branch Deep Convolutional Neural Network Architecture," Expert Systems with Applications, vol. 139, Article ID: 112854, DOI: 10.1016/j.eswa.2019.112854, 2019.

[42] P. J. Phillips et al., "Overview of the Multiple Biometrics Grand Challenge," Proc. of Advances in Biometrics (ICB 2009), Part of Lecture Notes in Computer Science, vol. 5558. Springer, Berlin, Heidelberg, [Online], Available: https://doi.org/10.1007/978-3-642-01793-3_72, 2021.

[43] J. Im, S. Jeon and M. Lee, "Practical Privacy-Preserving Face Authentication for Smartphones Secure Against Malicious Clients," in IEEE Transactions on Information Forensics and Security, vol. 15, pp. 2386-2401, DOI: 10.1109/TIFS.2020.2969513, 2020.

[44] S. Sengupta, J. Chen, C. Castillo, V. M. Patel, R. Chellappa and D. W. Jacobs, "Frontal to Profile Face Verification in the Wild," Proc. of the IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1-9, DOI: 10.1109/WACV.2016.7477558, Lake Placid, USA, 2016.

[45] T. Goel and R. Murugan, "Classifier for Face Recognition Based on Deep Convolutional Optimized Kernel Extreme Learning Machine," Computers & Electrical Engineering, vol. 85, Paper ID: 106640, DOI: 10.1016/j.compeleceng.2020.106640, 2020.

[46] T. Sim, S. Baker and M. Bsat, "The CMU Pose, Illumination and Expression Database," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1615-1618, Dec. 2003.

[47] A. Georghiades, P. Belhumeur and D. Kriegman, "Yale Face Database," Yale University, [Online] Available: http://cvc.yale.edu/projects/yalefaces/yalefa, 1997.

[48] F. Zhao, J. Li, L. Zhang, Z. Li and S. Na, "Multi-view Face Recognition Using Deep Neural Networks," Future Generation Computer Systems, vol. 111, pp. 375-380, DOI: 10.1016/j.future.2020.05.002, 2020.

[49] W. Gao et al., "The CAS-PEAL Large-scale Chinese Face Database and Baseline Evaluations," IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans, vol. 38, no. 1, pp. 149- 161, DOI: 10.1109/TSMCA.2007.909557, 2008. 

[50] A. Al-Shannaq and L. Elrefaei, "Age Estimation Using Specific Domain Transfer Learning," Jordanian Journal of Computers and Information Technology (JJCIT), vol. 06, no. 02, pp. 122-139, June 2020.

[51] S. Khan, M. H. Javed, E. Ahmed, S. A. A. Shah and S. U. Ali, "Facial Recognition Using Convolutional Neural Networks and Implementation on Smart Glasses," Proc. of the IEEE International Conference on Information Science and Communication Technology (ICISCT), pp. 1-6, Karachi, Pakistan, 2019.

[52] Z. Ren and X. Xue, "Research on Multi Pose Facial Feature Recognition Based on Deep Learning," Proc. of the 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), pp. 1427-1433, DOI: 10.1109/ICMCCE51767.2020.00313, Harbin, China, 2020.

[53] S. Khan, E. Ahmed, M. H. Javed, S. A. A Shah and S. U. Ali, "Transfer Learning of a Neural Network Using Deep Learning to Perform Face Recognition," Proc. of the International Conference on Electrical, Communication and Computer Engineering (ICECCE), pp. 1-5, Swat, Pakistan, 2019.

[54] Z. Lu, X. Jiang and A. Kot, "Deep Coupled ResNet for Low-resolution Face Recognition," IEEE Signal Processing Letters, vol. 25, no. 4, pp. 526-530, April 2018.

[55] G. Storey, R. Jiang, S. Keogh, A. Bouridane and C. Li, "DPalsyNet: A Facial Palsy Grading and Motion Recognition Framework Using Fully 3D Convolutional Neural Networks," IEEE Access, vol. 7, pp. 121655-121664, DOI: 10.1109/ACCESS.2019.2937285, 2019.

[56] S. Peng, H. Huang, W. Chen, L. Zhang, W. Fang, "More Trainable Inception-ResNet for Face Recognition," Neurocomputing, vol. 411, pp. 9-19, DOI: 10.1016/j.neucom.2020.05.022, 2020.

[57] B. Li and D. Lima, "Facial Expression Recognition via ResNet-50," International Journal of Cognitive Computing in Engineering, vol. 2, pp. 57-64, DOI: 10.1016/j.ijcce.2021.02.002, 2021.

[58] H. Wang, D. Zhang and Z. Miao, "Fusion of LDB and HOG for Face Recognition," Proc. of the 37th IEEE Chinese Control Conf., pp. 9192-9196, DOI: 10.23919/ChiCC.2018.8483900, Wuhan, China, 2018.

[59] M. A. Talab, S. Awang and S. A. M. Najim, "Super-low Resolution Face Recognition Using Integrated Efficient Sub-pixel Convolutional Neural Network (ESPCN) and Convolutional Neural Network (CNN)," Proc. of the IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS), pp. 331-335, DOI: 10.1109/I2CACIS.2019.8825083, Selangor, Malaysia, 2019.

[60] R. Gross, I. Matthews, J. Cohn, T. Kanade and S. Baker, "Multi-PIE," Image and Vision Computing, vol. 28, no.5, pp. 807-813, doi:10.1016/j.imavis.2009.08.002, 2010.