Student Attendance Recording Using Smart Camera Sensor

Recently, studies about face detection technology has been already reach its advanced state. In computer vision field of study, face detection technology is often used to identify someone by imitating how human eye works. Generally speaking, researches on face detection technology utilize regular camera which is embedded with image processing algorithm for image sequence. The approach is different when depth camera is used in face detection study. The process of detection using depth camera is also aided by infrared sensor which provides distance (depth) information and three-dimensional imaging of the object. The purpose of this paper is to design and develop a prototype of student attendance record application. Depth camera is used as an input tool to facilitate the face detection process. The resulting images from depth camera will be processes further in order to recognize student’s facial shape. To be able to identify student identity, the face detection process is done using facial geometric approach. This paper will address few issues regarding person identification such as the variation of human face condition (adjustment to the pattern) and variation of the camera position relative to the identify subject. The accuracy of the detection process is calculated to measure overall system success rate. This paper proposes the utilization of depth camera and implements it in a prototype of student attendance record application. Our proposed prototype can accelerate student attendance recording process compared to manual attendance recording process using paper. During several tests, our prototype also shows that it can successfully identify student face both in multi-view and multi-person scenarios.