Method for Detecting Student Classroom Learning Fatigue Based on Optical and Infrared Images

In classroom teaching, it is important for teachers to notice promptly the learning fatigue lever of students for the improvement of teaching quality. The fatigue of learners in classroom learning reflects their interest in learning, the difficulty of knowledge understanding, and the degree of mastery of knowledge. Thus, we developed an optical and infrared image fusion system to describe the fatigue level of students in the classroom using face segmentation technology and eye area positioning technology in image processing. In this system, the student's facial image was taken with a color lens and an infrared lens installed about 50 cm in front of the desk. Changes in marks on the student's face and segments in the eye area were detected by calculating eye aspect ratio, eye closure time, blink rate, and color. By fusing optical and infrared images, the color and infrared features were detected according to the change in intensity of light. The fusion matrix was created to estimate the impact of the light on fatigue detection. The experiment results verified a high accuracy in the detection of student fatigue. After detecting the degree of fatigue of students, teachers can adjust teaching content or teaching methods to maximize the quality of classroom teaching.