Abstract
This paper proposes a novel FRTDS (Face Recognition and Temperature Detection System) that is contactless and performs real-time face recognition. The system had proved to be fast, built at low-cost, and efficient in user authentication. FRTDS consists of numerous algorithms and techniques that have been implemented to improve the performance of the entire system with the help of Deep Neural Networks. FRTDS can capture images from a video stream and can detect faces from 70–90 cm away from the camera. An interactive front-end recognizes and displays the identity of the person. FRTDS also includes a temperature sensor to monitor the health of the person, before they enter any premises. The recognized face along with temperature data is stored at the back-end with the current time and date. This paper also presents a novel customized tool that eases the process of dataset creation and augmentation, and a novel prediction discrepancy elimination algorithm.
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References
M. Cheung, L. Chan, I. Lauder, C. Kumana, Detection of body temperature with infrared thermography: accuracy in detection of fever. Hong Kong Med. J. = Xianggang Yi Xue za Zhi/Hong Kong Acad. Med. 18(Suppl 3), 31–4 (2012)
R. Liao, S.Z. Li, Face recognition based on multiple facial features, in Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) (2000) pp. 239–244. https://doi.org/10.1109/AFGR.2000.840641
W. Zhao, R. Chellappa, A. Krishnaswamy, Discriminant analysis of principal components for face recognition, in Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition (1998), pp 336–341, https://doi.org/10.1109/AFGR.1998.670971
B.T. Chinimilli, T. Anjali, A. Kotturi, V.R. Kaipu, J.V. Mandapati,Face recognition based attendance system using Haar cascade and local binary pattern histogram algorithm, in 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184) (2020), pp. 701–704. https://doi.org/10.1109/ICOEI48184.2020.9143046
C. Chen, Y. Zhan, C. Wen, Hierarchical face recognition based on SVDD and SVM. Int. Conf. Environ. Sci. Inf. Appl. Technol. 2009, 692–695 (2009). https://doi.org/10.1109/ESIAT.2009.139
R. Senthilkumar, R. K. Gnanamurthy, Performance improvement in classification rate of appearance based statistical face recognition methods using SVM classifier, 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS) (2017), pp. 1–7, https://doi.org/10.1109/ICACCS.2017.8014584
G. Guo, S.Z. Li, K. Chan, Face recognition by support vector machines, in Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) (2000), pp. 196–201. https://doi.org/10.1109/AFGR.2000.840634
S. Nasr, K. Bouallegue, M. Shoaib, H. Mekki, Face recognition system using bag of features and multi-class SVM for robot applications, in 2017 International Conference on Control, Automation and Diagnosis (ICCAD) (2017), pp. 263–268. https://doi.org/10.1109/CADIAG.2017.8075668
C. Ding, D. Tao, Trunk-Branch ensemble convolutional neural networks for video-based face recognition, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 4 (2018), pp. 1002–1014. 1 Apr 2018. https://doi.org/10.1109/TPAMI.2017.2700390
D. Wang, H. Yu, D. Wang, G. Li, Face recognition system based on CNN. Int. Conf. Comput. Inf. Big Data Appl. (CIBDA) 2020, 470–473 (2020). https://doi.org/10.1109/CIBDA50819.2020.00111
T. Mantoro, M.A. Ayu, Suhendi, Multi-faces recognition process using Haar cascades and Eigenface methods, in 2018 6th International Conference on Multimedia Computing and Systems (ICMCS) (2018), pp. 1–5, https://doi.org/10.1109/ICMCS.2018.8525935
M.S.I. Sameem, T. Qasim, K. Bakhat, Real time recognition of human faces. Int. Conf. Open-Source Syst. Technol. (ICOSST) 2016, 62–65 (2016). https://doi.org/10.1109/ICOSST.2016.7838578
A.K. Jain, B. Klare, U. Park, Face recognition: Some challenges in forensics. IEEE Int. Conf. Autom. Face Gesture Recognit. (FG) 2011, 726–733 (2011). https://doi.org/10.1109/FG.2011.5771338
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M, V., Durai, P. (2022). A Novel Automated Human Face Recognition and Temperature Detection System Using Deep Neural Networks—FRTDS. In: Nayak, J., Behera, H., Naik, B., Vimal, S., Pelusi, D. (eds) Computational Intelligence in Data Mining. Smart Innovation, Systems and Technologies, vol 281. Springer, Singapore. https://doi.org/10.1007/978-981-16-9447-9_13
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DOI: https://doi.org/10.1007/978-981-16-9447-9_13
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