Mask and Emotion: Computer Vision in the Age of COVID-19

- Semerikov, Serhiy O. (orcid.org/0000-0003-0789-0272), Vakaliuk, Tetiana (orcid.org/0000-0001-6825-4697), Mintii, I.S. (orcid.org/0000-0003-3586-4311), Hamaniuk, Vita (orcid.org/0000-0002-3522-7673), Soloviev, V.N. (orcid.org/0000-0002-4945-202X), Bondarenko, O.V. (orcid.org/0000-0003-2356-2674), Nechypurenko, Pavlo P. (orcid.org/0000-0001-5397-6523), Shokaliuk, S.V. (orcid.org/0000-0003-3774-1729), Moiseienko, Natalia (orcid.org/0000-0002-3559-6081) and Ruban, Vitalii R. (orcid.org/0000-0001-9321-6086) (2022) Mask and Emotion: Computer Vision in the Age of COVID-19 DHW 2021: Digital Humanities Workshop, Kyiv, Ukraine, 23 December 2021. pp. 103-124.

Text paper38.pdf Download (29MB)

Abstract

Computer vision systems since the early 1960s have undergone a long evolution and are widely used in various fields, in particular, in education for the implementation of immersive educational resources. When developing computer vision systems for educational purposes, it is advisable to use the computer vision libraries based on deep learning (in particular, implementations of convolutional neural networks). Computer vision systems can be used in education both under normal and pandemic conditions. The changes in the education industry caused by the COVID-19 pandemic have affected the classic educational applications of computer vision systems, modifying existing ones and giving rise to new ones, including social distancing, face mask recognition, intrusion detection in universities and schools, and vandalism prevention, recognition of emotions on faces with and without masks, attendance monitoring. Developed on the basis of Microsoft Cognitive Toolkit and deployed in the Microsoft Azure cloud, a prototype computer vision system integrates emotion recognition of students and detection of violations of the mask regime, additionally providing the ability to determine gender, smile intensity, average age, makeup, glasses, hair color, etc. with a high degree of reliability.

Item Type:	Article
Keywords:	computer vision, COVID-19, education, mask detection
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.5 Human-computer interaction. Man-machine interface. User interface. User environment Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 ІКТ ( Application-oriented computer-based techniques ) > 004.92 Computer graphics Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 ІКТ ( Application-oriented computer-based techniques ) > 004.93 Pattern information processing
Divisions:	Institute for Digitalisation of Education > Department of Cloud-Oriented Systems and Artificial Intelligence in Education
Depositing User:	Сергій Олексійович Семеріков
Date Deposited:	06 Jan 2023 17:09
Last Modified:	06 Jan 2023 17:09
URI:	https://lib.iitta.gov.ua/id/eprint/733722

Downloads

Actions (login required)

View Item