Drowsiness Detection and Head Pose Estimation in Online Learning Platforms with Image Processing

Abstract

The concept of education, which has existed for hundreds of years, is being moved to online environments, especially with the increase in internet use. Although the use of internet-based applications in education increases accessibility to information, it makes it difficult to evaluate students' performances fairly. In recent years, the number of image processing studies on this subject has been increasing in order to take online education platforms to the next level. In this study, fatigue estimation was made to measure the performance of students in distance education systems. Some machine learning and image processing methods were used for fatigue prediction. In the proposed study, two different data sets consisting of 15182 images were used. Python and Flask framework are used in model training. A web-based application was developed with Flask that performs real-time fatigue detection and head position estimation via webcam.

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