Uddin, JiaIslam, Md. ShafiqulMahmud, AsifPapeya, Azmina AkterOnny, Irin Sultana2017-06-142017-06-1420174/18/2017ID 13101119ID 13101208ID 13101234ID 13301098http://hdl.handle.net/10361/8242Cataloged from PDF version of thesis report.Includes bibliographical references (page 26 - 29).This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.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.29 pagesenBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Classroom attendanceClassroom managementThesis