Students’ Attendance Monitoring through the Face Recognition

This paper describes experimental software solution for monitoring of students' attendance through the face detection and recognition in the video. The analysis of existing face detection and recognition algorithms was carried out, and the design of the system solution is described, implementing the previously analyzed algorithms. The Viola-Jones algorithm and HOG are used to detect the face in the video. To recognize an identity of a student, the convolutional neural network (NN) is utilized. The system was tested in the real university environment on selected courses. Once the face recognition is finished, the attendance list of present people may be generated. The system then provides additional visual verification of recognized faces to the lecturer (administrator).