The Application of Image Processing for Monitoring Students’ Attention Level during an Online Class
The aim of this project is to create an algorithm that is able to monitor both facial expression and eye movement of a student during online lecture classes. The information can then be used to help lecturers determine the attention level of each student in class.
The year 2020 has seen the world fighting against the covid-19 pandemic. With everyone being quarantined in their homes, this mean that lecture classes will have to be conducted online. However, with this new setup, lecturers are having a hard time determining the attention level of a student. Therefore, an algorithm that is able to monitor both facial expression and eye movement is proposed to determine a student’s attention level during classes. The Viola-Jones face detection and Hough transform will be applied to create the new algorithm. Viola-Jones is a well-known facial detection algorithm that applies the Haar-like features to detect the position of the face. The Hough algorithm will then be used to detect the edges in the image and track the movement of that person. Once the face is detected, the movement of the eye and the expression of that person will be determined. All of the data will be collected and analysed using the MATLAB software. It is expected that the proposed algorithm can be applied to any existing webcam to collect and examine the data to determine the attention level of the students and send a notification to the lecturer if the student is not paying attention.