Recognition of student’s attendance automatically is a challenging task. In this paper, we proposed a system that takes attendance of the students for classroom lecture by detecting and recognizing the face automatically using k nearest neighbor algorithm (KNN). However, it is difficult to estimate the attendance precisely using each result of face recognition autonomously for the reason that the face detection rate is not deficiently high. Hence, we proposed a method for estimating the attendance literally using all the outcomes of face recognition achieved by continuous observation. Continuous observation improves the performance for the estimation of the attendance. We constructed the enhanced visual attendance system based on face detection and recognition, and adapted the system to the classroom. This paper first review the related works in the field of attendance management and face recognition. Then, it introduces our system structure and plan. Finally, the system is enforced to provide as testimony to support our proposal. The result demonstrates that continuous observation enhanced the attainment for the estimation of student’s attendance.
Volume 11 | 06-Special Issue
Pages: 141-147