Classroom Attendance System based on Face Recognition
Pranav Gupte, Sheldon Rodrigues, Priya Singh, Anagha Shastri
MTCNN, Facenet, Face Detection, Face Recog- nition, Image processing
Currently, teachers have to manually take the at- tendance of students leading to wastage of lecture time and detachment from the flow of lecture. The limitations in automated attendance systems making use of clickers, ID card swiping and manually marking attendance has prompted this project to be carried out. The Classroom Attendance System aims to facilitate classroom control and attendance by detecting and recognising students’ faces in a digital image or video taken by a camera. It designates the manual process of marking attendance by a lecturer to an automated system which saves time, removes paper dependency for marking attendance and ensures a more efficient mode of taking attendance. The main goal is to relieve the lecturers from taking attendance manually and automate the process. A camera is used as a source of data required for face detection. The background processing of the data is done on a remote computer wherein the complete list of students’ attendance is generated. The system also provides the tools that simplify the process of making custom face recognition models for different classrooms. It uses MTCNN for face detection and a pre-trained Facenet model for face recognition. The experimental results verify that FaceNet can meet the requirements of real-time recognition of highest accuracy and can be effectively applied to face detection and recognition in the Classroom Attendance System.
Article Details
Unique Paper ID: 160844

Publication Volume & Issue: Volume 10, Issue 1

Page(s): 1445 - 1451
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