ClassScan: Simplifying Classroom Attendance using Three-Dimensional Dense Face Alignment and Face Recognition
Sanket Salvi, Jain S. A. Pramod · 2023
Managing attendance in classrooms is a critical task that often relies on manual processes, leading to inefficiencies and potential inaccuracies. In this study, we address this challenge by proposing a web-based face recognition attendance system. Our solution encompasses key functionalities such as student registration, face extraction, and detection, student and teacher login, attendance tracking, and reporting. By using a face recognition method that generates a 3D face using TDDFA algorithm, our system showcased an accuracy rate of 95.0%. Furthermore, the average time required for attendance marking is significantly reduced to just 2.3 seconds/student, offering a rapid and streamlined process compared to traditional manual methods. User feedback from faculty members highlights a high level of satisfaction, with an average usability rating of 4.2 out of 5. The proposed face recognition attendance system provides an efficient solution and thus addresses the challenges associated with manual attendance management in classrooms.