Paper Info
Title
CVUCAMS: Computer Vision Based Unobtrusive Classroom Attendance Management System
Abstract
One of the major challenges in a smart classroom environment is to develop a computer vision based unobtrusive classroom attendance management system. Traditional classroom environment follows a manual attendance marking system either by calling the student's names or by forwarding an attendance sheet; both interrupts the teaching-learning process and also consume a lot of time. Further, it can be erroneous due to factors such as students' proxy etc. In this paper, we propose an unobtrusive face recognition based smart classroom attendance management system using the high definition rotating camera for capturing the faces of students. The proposed system uses Max-Margin Face Detection (MMFD) technique for the face detection and the model is trained using the Inception-V3 CNN technique for the students' identification. The proposed smart classroom system was tested for a classroom with 20 students at National Institute of Technology Karnataka Surathkal, Mangalore, India and we got the experimental results demonstrate the train and test accuracy of 97.67% and 96.66%, respectively.
Year
DOI
Venue
2018
10.1109/ICALT.2018.00131
2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)
Keywords
Field
DocType
Max Margin Face Detection, Object Tracking, Face Recognition, Inception V3
Proxy (climate),Computer vision,Facial recognition system,High definition,Attendance management system,Computer science,Artificial intelligence,Face detection,Smart classroom,Attendance,Multimedia
Conference
ISSN
ISBN
Citations 
2161-3761
978-1-5386-6050-8
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Sujit Kumar Gupta130.73
Ashwin T. S200.34
Ram Mohana Reddy Guddeti3488.76