SUBJECT BEHAVIOR DETECTION AND ANALYSIS BASED ON COMPUTER VISION TECHNOLOGY

Authors

DOI:

https://doi.org/10.37943/UIXY4934

Keywords:

distance learning, face detection, proctoring

Abstract

This article discusses the current problem of identifying violations during distance learning during the final certification.

The coronavirus (COVID-19) pandemic has served as a stimulus for innovation in the field of education in all countries, including Kazakhstan. Innovative approaches are being taken to ensure the continuity of education and training. Thanks to the rapid response measures taken by governments and partners around the world to ensure the smooth learning process. The ongoing digital transformation of an educational institution requires appropriate information content, suitable methodological models, effective teaching methods and a supportive learning environment. The solution to one of the urgent tasks is to ensure the quality and reliability of assessing the knowledge of students by introducing an online proctoring system. The primary task of the online proctoring system is to recognize faces and identify abnormal behavior of students.

The basis for obtaining data is the unified information educational environment of the D. Serikbayev East Kazakhstan Technical University is represented by the SPORTAL hardware and software system, which is an integration of two powerful subsystems: a Web application - the Dales of Knowledges educational portal and the SPORTAL information and software complex.

The main theoretical results obtained are aimed at solving practical problems and are being introduced into the educational environment of D. Serikbayev East Kazakhstan Technical University to increase the degree of confidence in the results of students' knowledge in distance learning using an online proctoring system. The article presents the results of studies of one of the Viola-Jones face detection methods, commonly known as Haar cascades. During the study, a technology for identifying faces and detecting violations in real time was developed. Domestic and foreign scientists who have made a significant contribution to the development of methods for processing facial images are noted.

Author Biographies

D. Muratuly, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan

3rd year doctoral student of the educational program "Information Systems"

N. Denissova, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan

Candidate of physical and mathematical sciences, Vice-Rector for Research and Digitalization

I. Krak, Taras Shevchenko National University of Kyiv, Ukraine

Doctor of Physical and Mathematical Sciences, Head of the Department of Theoretical Cybernetics

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Published

2022-09-30

How to Cite

Muratuly, D., Denissova, N., & Krak, I. (2022). SUBJECT BEHAVIOR DETECTION AND ANALYSIS BASED ON COMPUTER VISION TECHNOLOGY. Scientific Journal of Astana IT University, 11(11), 36–47. https://doi.org/10.37943/UIXY4934

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