Face Recognition-Based Mobile Automatic Classroom Attendance Management System

SAMET R., Tanriverdi M.

International Conference on Cyberworlds (CW), Chestermere, Kanada, 20 - 22 Eylül 2017, ss.253-256 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/cw.2017.34
  • Basıldığı Şehir: Chestermere
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.253-256
  • Anahtar Kelimeler: face detection, face recognition, eigenfaces, fisherfaces, local binary pattern, attendance management system, mobile application, accuracy, PERFORMANCE
  • Ankara Üniversitesi Adresli: Evet

Özet

Classroom attendance check is a contributing factor to student participation and the final success in the courses. Taking attendance by calling out names or passing around an attendance sheet are both time-consuming, and especially the latter is open to easy fraud. As an alternative, RFID, wireless, fingerprint, and iris and face recognition-based methods have been tested and developed for this purpose. Although these methods have some pros, high system installation costs are the main disadvantage. The present paper aims to propose a face recognition-based mobile automatic classroom attendance management system needing no extra equipment. To this end, a filtering system based on Euclidean distances calculated by three face recognition techniques, namely Eigenfaces, Fisherfaces and Local Binary Pattern, has been developed for face recognition. The proposed system includes three different mobile applications for teachers, students, and parents to be installed on their smart phones to manage and perform the real-time attendance-taking process. The proposed system was tested among students at Ankara University, and the results obtained were very satisfactory.