Facial Recognition for Attendance Monitoring – A Prototype

Abstract

All Educational Institutions prioritize student attendance and Baze University is certainly one to uphold the standard. All students are required to maintain a minimum attendance rate of at least 75% in each class or lecture to be eligible to take the module's examination. With the advancement of technology, biometrics concepts have proven to be more efficient in monitoring attendance. We present a facial recognition-based prototype webapp for Baze university. This webapp aims to eradicate the cumbersome method of marking attendance that lecturers of Baze University have subscribed to. The main focus is the use of facial recognition techniques using the Dlib library of OpenCV. Images are read and stored in a database, compared with images captured from a webcam to analyze and record the best matches using nearest neighbor algorithm.