Face Recognition for Attendance System using CNN based Liveliness Detection
Abhishek Potdar, Parva Barbhaya, Sangeeta Nagpure · 2022
The high-speed development of the technology behind facial recognition systems has enabled its usage in the application to record attendance without human interference. The advantage of the software lies in its security, authentication, and identification features. The paper proposes one such attendance system for educators. The five phases of the attendance system are database creation of students, face detection, liveliness detection, face recognition, and attendance marking. The database is created by the images of the students in class. One of its distinguishing features is the liveliness detection algorithm, which solves the proxy attendance problem. Liveliness detection is performed using blinking detection and CNN classification between real and spoof images. The accuracy obtained from the system is 93%. Further, face recognition is performed using FaceNet. A web-based application is developed to make attendance marking more convenient for educators.