Real time classroom attendance management system

Abstract

Face recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. Classroom attendance management system is one of the applications. Traditional attendance system: roll calling, card punching, paper-based attendance are manual process. It takes a lot of time. To remove hectic of traditional process Real time attendance management system is a better solution. Without physical interaction of human being it gives the attendance of present student in the class. Using Kinect camera we took the video input of the classroom. Detection of human face from the video stream is done by Viola- Jones algorithm. For recognition purpose we tested Speeded Up Robust Features (SURF), Histogram of Oriented Gradients (HOG), Linear Binary Pattern (LBP) feature extraction algorithm and do some comparison between those algorithm for our created dataset. In order to normalization we used Kernel Based Filtering method. In our work, when a face of a student matches with the face of dataset it marked the student as present.