LIU, YU-MING
The Department of Multimedia Design of National Taichung University of Science and Technology Graduate Student
Email：yuming4142@gmail.com
SHYU,FONG-MING
The Department of Multimedia Design of National Taichung University of Science and Technology Associate Professor
Email：fms@nutc.edu.tw
Abstract
In 2020, in response to the COVID-19 (new coronavirus pneumonia) epidemic that has swept the world, many students studying abroad have been affected by this and cannot study in school. This wave of epidemic has given a new definition of distance teaching, and this impact has promoted academics. The institution develops and invests in new online course resources. Although remote teaching is convenient, the epidemic also brings new challenges to students’ learning and employment. At this time, the system studied in the paper that judges the concentration of most users through image analysis can achieve substantial help. Facial images have been obtained through the video lens, and after comprehensive analysis of facial feature recognition and blink detection, the faculty members can obtain the concentration analysis of the students in the classroom; it can also achieve the self-detection of the users themselves, and obtain the evaluation and self-detection through these data the goal of. This study achieved 85.2% of face recognition rate and then obtained nearly 90% of concentration detection accuracy through blink detection. The accuracy rate is suitable for the detection and evaluation of online learning.
Keywords :classroom observation, online learning, attention assessment, facial features recognition, blink detection