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Face detection and recognition of mask wearing in normal environment based on neural network
- 1 School of Information Engineering Shanghai Maritime University, Shanghai, 201306, China
- 2 School of Physics, Xi’an JiaoTong University, Xian, Shaanxi, 710049, China
- 3 University of Liverpool, Liverpool L1 8JX, UK
- 4 epartment of International Baccalaureate Diploma Programme, Shanghai World For-eign Language Academy, Shanghai, 200233, China
* Author to whom correspondence should be addressed.
Abstract
With the outbreak of COVID-19, wearing masks has become a hot topic again. In public places, Not wearing a mask correctly has almost the same harm as not wearing a mask. Mask detection is an extension of face detection. Therefore, it is of great practical signifi-cance to design a system that can correctly identify whether pedestrians wear masks cor-rectly. The face recognition technology based on neural network has been relatively ma-ture, but there is still a lack of work related to mask recognition, especially whether to wear masks correctly. This is not only the promotion of a two-classification problem to a three-classification problem, but also faces many practical problems, including data set acquisition, in this paper, mask recognition is divided into a multi-stage work. In the first link, Yolo network is used to recognize facial areas, and in the second link, RESNET is used to realize mask recognition. Finally, a layer of RESNET network is improved to achieve higher recognition accuracy.
Keywords
COVID-19, face detection, mask detection, Yolo network, RESNET
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Cite this article
Li,Y.;Xie,S.;Ren,Y.;Li,X. (2023). Face detection and recognition of mask wearing in normal environment based on neural network. Applied and Computational Engineering,2,21-30.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
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