TY - GEN
T1 - Automatic attendance capturing using histogram of oriented gradients on facial images
AU - Ade-Ibijola, Abejide
AU - Aruleba, Kehinde
N1 - Publisher Copyright:
© 2018 IST-Africa Institute.
PY - 2018/7/20
Y1 - 2018/7/20
N2 - 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.
AB - 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.
KW - Face recognition
KW - Feature extraction
KW - Histogram of oriented gradients
UR - http://www.scopus.com/inward/record.url?scp=85051207427&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85051207427
T3 - 2018 IST-Africa Week Conference, IST-Africa 2018
BT - 2018 IST-Africa Week Conference, IST-Africa 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IST-Africa Week Conference, IST-Africa 2018
Y2 - 9 May 2018 through 11 May 2018
ER -