PRESENT an automatic classroom attendance checker implementing SVM for face recognition and face detection - Lasa, Carlos Miguel M.; Maximo, Eunice Grace G.; Pugoy, Luis Manuel R. (2006)
Research and experience have shown that class attendance is statistically significant in explaining class grade and overall performance of students in educational institutions. Regular and punctual attendance in class is considered a variable for quality performance. One problem faced by educators in this field is attendance checking. The most popular methods that are implemented are roll calls and sign-up sheets. These two methods are usually faulty because of human error (e.g. failing to hear one's name called, failing to sign on the sign-up sheet). Aside from that, manual methods inefficiently take away time used for teaching in the classroom. In this paper, a system to automatically check the attendance of students in a classroom environment is proposed. This is done through the detection and recognition of human faces present in images taken from captured video. The system can be divided into two phases: face detection and face recognition. Both shall be implemented using a learning technique called Support Vector Machines (SVM). The face detection phase aims to discriminate between faces and non-faces present in the captured video images. The detected faces shall be then passed on to the face recognition phase, which will tehn discriminate one face from another by comparing the faces to a database containing images of students enrolled in a certain class.
Thesis (B.S. Computer Science)--University of the Philippines, Diliman.
Keywords: Human face recognition (Computer science); Support vector machines; PRESENT