Automatic Attendance Capturing Using Histogram of Oriented Gradients on Facial Images
Abejide Ade-Ibijola, Kehinde Aruleba · IST-Africa Week Conference · 2018
Humans mostly use faces to identify/recognise individuals and the recent improvement in the capability of computing now allow recognition and detection automatically. However, there still exist quite a number of problems in the automatic recognition of facial images. Histogram of Oriented Gradients (HOG) has been recently adopted and seen as a standard for efficient face recognition and object detection generally. In this paper, we investigate and discuss a simple but effective approach to capturing student’s attendance register in a lecture hall by making use of HOG features for detecting and recognising students face at different moods, orientations, and illuminations. Our experiment detection and recognition output show a good performance on our facial image database obtained from the University of Johannesburg, this performance is due to HOG descriptors attributes which are robust to changes in rotation and illuminations. Our system will help to save instructional staff/lecturer time by eliminating manual calling of students name and also help monitor students.