The week's pick
Reseach Article
Survey towards Masked Face Detection for Pandemic
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 8 |
| Year of Publication: 2021 |
| Authors: Yash Agrawal, Diksha Nitnaware, Gauri Kulkarni, Saurabh Patil, Archana Lomte |
10.5120/ijca2021921370
|
Yash Agrawal, Diksha Nitnaware, Gauri Kulkarni, Saurabh Patil, Archana Lomte . Survey towards Masked Face Detection for Pandemic. International Journal of Computer Applications. 183, 8 ( Jun 2021), 18-21. DOI=10.5120/ijca2021921370
Abstract
Covid19 has given another personality for wearing a veil. It is significant when these covered countenances are recognized precisely and proficiently. As an exceptional face recognition task, face veil identification is substantially more troublesome on account of outrageous impediments which prompt the deficiency of face subtleties. Furthermore, there is basically no current enormous scope precisely marked concealed face dataset, which increments the trouble of face veil discovery. The framework urges to utilize CNN-based profound learning calculations which have done tremendous advancement towards explores in face identification. In this paper, propose a novel CNN-based technique that is shaped by three convolutional neural organizations to recognize the face veil. Plus, in view of the deficiency of face veiled preparing tests, propose another dataset called" face cover dataset" to tweak CNN models. Assess proposed face veil recognition calculation on the face cover testing set, and it accomplishes agreeable execution.
References
- Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Spatial pyramid pooling in deep convolutional networks for visual recognition. In European Conference on Computer Vision, pages 346–361. Springer,2014
- Wei Bu, Jiangjian Xiao, Chuanhong Zhou, Minmin Yang, Chengbin Peng A Cascade Framework for Masked Face Detection, IEEE 8th International Conference on CIS & RAM, Ningbo, China, 2017.
- X. Xu, L. Zhang and F. Li, "MSSVT: Multi-scale feature extraction for single face recognition," 2018 24th International Conference on Pattern Recognition (ICPR), Beijing, 2018, pp. 1996-2001, doi: 10.1109/ICPR.2018.8545343.
- Lun Zhang, Rufeng Chu, Shiming Xiang, Shengcai Liao, and Stan Z Li. Face detection based on multi-block lbp representation. In International Conference on Biometrics, pages 11–18. Springer, 2007.NaliniPriya G, Priyadarshani P, RajaRajeshwari K, IEEE 6thInternational Conference on smart structures and systems ICSSS 2019.
- C. Jiang, M. Wang, X. Tang and R. Mao, "Face recognition method based on sparse representation and feature fusion," 2019 Chinese Automation Congress (CAC), Hangzhou, China, 2019, pp. 396-400, doi: 10.1109/CAC48633.2019.8997456.
- Y. Zhou, H. Ni, F. Ren and X. Kang, "Face and Gender Recognition System Based on Convolutional Neural networks," 2019 IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China, 2019, pp. 1091-1095, doi: 10.1109/ICMA.2019.8816192.
- M. R. Reshma and B. Kannan, "Approaches on Partial Face Recognition: A Literature Review," 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 2019, pp. 538-544, doi: 10.1109/ICOEI.2019.8862783.
- M. S. Ejaz, M. R. Islam, M. Sifatullah and A. Sarker, "Implementation of Principal Component Analysis on Masked and Non-masked Face Recognition," 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), Dhaka, Bangladesh, 2019, pp. 1-5, doi: 10.1109/ICASERT.2019.8934543.’’
- E. Winarno, I. Husni Al Amin, H. Februariyanti, P. W. Adi, W. Hadikurniawati and M. T. Anwar, "Attendance System Based on Face Recognition System Using CNN-PCA Method and Real-time Camera," 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia, 2019, pp. 301-304, doi: 10.1109/ISRITI48646.2019.9034596.
- S. Sawhney, K. Kacker, S. Jain, S. N. Singh and R. Garg, "Real-Time Smart Attendance System using Face Recognition Techniques," 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2019, pp. 522-525, doi: 10.1109/CONFLUENCE.2019.8776934.
- W. Zeng, Q. Meng and R. Li, "Design of Intelligent Classroom Attendance System Based on Face Recognition," 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China, 2019, pp. 611-615, doi: 10.1109/ITNEC.2019.8729496.
Index Terms
Keywords