International Journal of Recent
Engineering Science

Research Article | Open Access | Download PDF
Volume 7 | Issue 3 | Year 2020 | Article Id. IJRES-V7I3P115 | DOI : https://doi.org/10.14445/23497157/IJRES-V7I3P115

A Review: Facial Recognition Using Machine


Pooja G Nair,Sneha R

Citation :

Pooja G Nair,Sneha R, "A Review: Facial Recognition Using Machine," International Journal of Recent Engineering Science (IJRES), vol. 7, no. 3, pp. 97-102, 2020. Crossref, https://doi.org/10.14445/23497157/IJRES-V7I3P115

Abstract

A facial recognition system can verify or identify a person from a video or a digital image. There are various techniques in which these systems work. Popularly, they work by first matching the facial characteristics picked from the image to the faces stored in the database. It is called a Biometric Identification based application that uniquely identifies each individual by analyzing their voice, face expression, face or fingerprint. Even though it was initially used as a computer application, it has gained broader uses in mobile platforms and other technology sectors, such as robotics. It has a huge application in security systems. Although the accuracy of this system as a biometric technology is lower than that of fingerprint recognition and iris detection, it is broadly used due to its non-invasive and contactless features. It has recently grown in significance as a tool for retail and marketing. Another application is video surveillance to identify missing people or criminals. It is gaining importance in the healthcare sector. Facial recognition technology has become very popular and is being used everywhere from shopping centers, airports, venues and by law enforcement. This technology can also be used to prevent crimes such as shoplifting by identifying ex-cons. Although this technology is gaining widespread use there are many concerns about privacy and safety.

Keywords

Convoluted Neural Networks, Facial Recognition, Machine Learning, Support Vector Machine. 

References

[1] S. Kim, G. H. An and S. Kang., Facial expression recognition system using machine learning, International SoC Design Conference (ISOCC), Seoul.(2017).
[2] E. García Amaro, M. A. Nuño-Maganda and M. MoralesSandoval., Evaluation of machine learning techniques for face detection and recognition, CONIELECOMP 22nd International Conference on Electrical Communications and Computers, Cholula, Puebla.(2012).
[3] D. V. Sang, N. Van Dat, and D. P. Thuan., Facial expression recognition using deep convolutional neural networks, 9th International Conference on Knowledge and Systems Engineering (K.S.E.), Hue. (2017).
[4] A. Vinay., Face recognition using interest points and ensemble of classifiers, 4th International Conference on Recent Advances in Information Technology (RAIT), Dhanbad.(2018).
[5] Q. Liu, P. Li, W. Zhao, W. Cai, S. Yu, and V. C. M. Leung., A Survey on Security Threats and Defensive Techniques of Machine Learning: A Data-Driven View, IEEE Access.6 (2018) 12103- 12117.
[6] Xue-Fei Bai and Wen-Jian Wang., An approach for facial expression recognition based on neural network ensemble, International Conference on Machine Learning and Cybernetics, Hebei.(2009).
[7] M. Ishii., Basic research on facial expression recognition model with adaptive learning capability, IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, AK.(2011).
[8] Mullainathan Sendhil and Spiess Jann., Machine Learning: An Applied Econometric Approach, Journal of Economic Perspectives, 31(2017) 87-106.
[9] T. Kundu and C. Saravanan., Advancements and recent trends in emotion recognition using facial image analysis and machine learning modInternational Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), Mysuru. (2017).
[10] A. Mostafa, M. I. Khalil, and H. Abbas., Emotion Recognition by Facial Features using Recurrent Neural Networks, 13th International Conference on Computer Engineering and Systems (ICCES), Cairo, 2018.
[11] Coşkun, Musab & Uçar, Ayşegül & yıldırım, Özal & Demir, Yakup, Face Recognition Based on Convolutional Neural Network, (2017).
[12] J. C. T. Kwong, F. C. C. Garcia, P. A. R. Abu, and R. S. J. Reyes., Emotion Recognition via Facial Expression: Utilization of Numerous Feature Descriptors in Different Machine Learning Algorithms, TENCON IEEE Region 10 Conference, Jeju, Korea (South).(2018).
[13] X. Han and Q. Du., Research on face recognition based on deep learning Sixth International Conference on Digital Information, Networking, and Wireless Communications (DINWC), Beirut, (2018).
[14] Farhad Navabifar, Mehran Emadi, Rubiyah Yusof and Marzuki Khalid., A short review paper on Face detection using Machine learnin. (2011).
[15] Stephen Balaban., Deep learning and face recognition: the state of the art.( 2015).
[16] Bhumika Pathya, Sumita Nainan., Performance Evaluation of Face Recognition using LBP, P.C.A. and SVM”.SSRG International Journal of Computer Science and Engineering 3(4) (2016).