Real-Time Group Face-Detection for an Intelligent Class-Attendance System

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Author(s)

Abdelfatah Aref Tamimi 1,* Omaima N. A. AL-Allaf 2 Mohammad A. Alia 3

1. Faculty of Sciences & IT, Al-Zaytoonah University of Jordan, Dept. of Computer Science, P.O. Box130, Amman (11733), Jordan

2. Faculty of Sciences & IT, Al-Zaytoonah University of Jordan, Dept. of Basic Sciences, P.O. Box130, Amman (11733), Jordan

3. Faculty of Sciences & IT, Al-Zaytoonah University of Jordan, Dept. of Computer Information Systems, P.O. Box130, Amman (11733), Jordan

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2015.06.09

Received: 4 Oct. 2014 / Revised: 27 Jan. 2015 / Accepted: 23 Mar. 2015 / Published: 8 May 2015

Index Terms

Face Detection, Group Face Detection, Real-Time Face Detection, Attendance System

Abstract

The traditional manual attendance system wastes time over students’ responses, but it has worked well for small numbers of students. This research presents a real-time group face-detection system. This system will be used later for student class attendance through automatic student identification. The system architecture and its algorithm will be described in details. The algorithm for the system was based on analyzing facial properties and features in order to perform face detection for checking students’ attendance in real time. The classroom’s camera captures the students’ photo. Then, face detection will be implemented automatically to generate a list of detected student faces. Many experiments were adopted based on real time video captured using digital cameras. The experimental results showed that our approach of face detection offers real-time processing speed with good acceptable detection ratio equal to 94.73%.

Cite This Paper

Abdelfatah Aref Tamimi, Omaima N. A. AL-Allaf, Mohammad A. Alia, "Real-Time Group Face-Detection for an Intelligent Class-Attendance System", International Journal of Information Technology and Computer Science(IJITCS), vol.7, no.6, pp.66-73, 2015. DOI:10.5815/ijitcs.2015.06.09

Reference

[1]Jonathan Howell A. and Hilary Buxton, Face Recognition using Radial Basis Function Neural Networks, Proceedings of British Machine Vision Conference, 1996.

[2]Fei Zuo, Embedded Face Recognition Using Cascaded Structures, Thesis, Technische Univ Eindhoven, China, 2006.

[3]Anissa Bouzalmat, et. al, Face Recognition Using Neural Network Based Fourier Gabor Filters & Random Projection, International Journal of Computer Science and Security (IJCSS), vol.5, issue.3, pp.376- 386, 2011.

[4]Turk M. and Pentland A., Eigenfaces for recognition, Journal of Cognitive Neuroscience, vol.3, pp.71–86, 1991.

[5]Pushpaja V. Saudagare and D.S. Chaudhari, Facial Expression Recognition using Neural Network –An Overview, International Journal of Soft Computing and Engineering, vol.2, issue.1, pp.224-227, March 2012.

[6]Yao-Jiunn Chen, Yen-Chun Lin, Simple Face-detection Algorithm Based on Minimum Facial Features, The 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON) 5-8Nov 2007, Taiwan, pp.455-460.

[7]Sanjay Kr. Singh, et. al, A Robust Skin Color Based Face Detection Algorithm, Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp. 227-234, 2003.

[8]Abdenour Hadid, Matti Pietik¨ainen and Timo Ahone, A Discriminative Feature Space for Detecting and Recognizing Face, ACM, 2004.

[9]Elise Arnaud , et. Al, A Robust And Automa Tic F Ace Tracker Dedica Ted To Broadcast Videos, IEEE international conference on image processing, 2005.

[10]Zhonglong Z., Jie Y. and Yitan Z., Face Detection and Recognition using Colour Sequential Images , Journal of Research and Practice in Information Technology, Vol. 38, No. 2, pp.135-149, May 2006.

[11]E. Hjelmas and B. K. Low, Face Detection: A Survey, Computer Vision and Image Understanding, vol.83, pp. 236-274, 2001.

[12]Yongzhong Lu, Jingli Zhou, Shengsheng Yu, A Survey Of Face Detection, Extraction And Recognition, Computing and Informatics, Vol. 22, pp.163-195, 2003

[13]Ming-Hsuan Yan, et. Al, Detecting Faces in Images: A Survey, IEEE Transactions on Pattern Analysis And Machine Intelligence, Vol. 24, No. 1, pp.34-58, Jan2002.

[14]W. Zhao, R. Chellappa, A. Rosenfeld and P. Phillips. Face recognition: A literature survey, ACM Computing Surveys, Vol.35, No.4, Dec2003, pp. 399–458.

[15]Cha Zhang and Zhengyou Zhang, A Survey of Recent Advances in Face Detection June 2010, Technical Report, MSR-TR-2010-66, Microsoft Research, Microsoft Corporation One Microsoft Way, Redmond, WA 98052.

[16]Rob McCready, Real-Time Face Detection on a Configurable Hardware Platform, Master of Applied Science thesis in the Graduate Department of Electrical and Computer Engineering, University of Toronto, 2000.

[17]Paul V. and Michael J. Jones. Robust real-time object detection, Proc. of IEEE Workshop on Statistical and Computational Theories of Vision, 2001.

[18]G. Shakhnarovich, et al. A Unified Learning Framework for Real Time Face Detection and Classification, IEEE, Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGRí02), 2002.

[19]Paul V. and Michael J., Robust Real-Time Face Detection, International Journal of Computer Vision, 57(2), 137–154, 2004, Kluwer Academic Publishers. Netherlands.

[20]Mustafah, et. al, Real-Time Face Detection and Tracking for High Resolution Smart Camera System, Digital Image Computing Techniques and Apps, pp:387-393, 2007.

[21]Zhiwei Zhu and Qiang Ji, Robust real-time eye detection and tracking under variable lighting conditions and various face orientations, Computer Vision and Image Understanding, vol.98, pp:124–154, 2005.

[22]Michalis Zervos, Multi-camera face detection and recognition applied to people tracking, Master Thesis, January 2013, Education and Lifelong Learning of the European Social Fund (ESF) and the NSRF 2007-2013.

[23]Mohammad A. Alia, Abdelfatah Aref Tamimi and Omaima N. A. AL-Allaf, Integrated System for Monitoring and Recognizing Students During Class Session, AIRCC’s : International Journal of Multimedia & Its Applications (IJMA), Vol.5, No.6, Dec2013, pp:45-52.

[24]Vijay Lakshmi and PatilKulakarni, Segmentation Algorithm for Multiple Face Detection in Color Images with Skin Tone Regions using Color Spaces and Edge Detection Techniques, I. J. of Computer Theory and Eng., Vol. 2, No. 4, pp.552-558, August, 2010.

[25]V.K. Narendira Kumar and B. Srinivasan, Internet Passport Authentication System Using Multiple Biometric Identification Technology, I.J. Information Technology and Computer Science, 2013, 03, 79-89, 10.5815/ijitcs

[26]Arindam Kar, A Face Recognition Approach Based on Entropy Estimate of the Nonlinear DCT Features in the Logarithm Domain Together with Kernel Entropy Component Analysis, I.J. Information Technology and Computer Science, 09, pp:31-42, August 2013, MECS.

[27]Prakash C. S., et. al. Fingerprints, Iris and DNA Features based Multimodal Systems: A Review, I.J. Information Technology and Computer Science, 2013, 02, pp:88-111.

[28]Bell, John L. The Art of the Intelligible: An Elementary Survey of Mathematics in its Conceptual Development. 1999, Kluwer. ISBN 0-7923-5972-0.

[29]Euclid. Translated by Johan Ludvig Heiberg with an introduction and commentary by Sir Thomas L. Heath, ed. 1956, The Elements (3vols.) (I and II)

[30]Heath, Sir Thomas. The Theorem of Pythagoras. A History of Greek Mathematics (Vol.2., 1921) (Dover Publications, Inc. (1981) ed.). Clarendon Press, Oxford. pp:144, pp:321-323, ISBN 0-486-24073-8.

[31]Sterbenz P., Pat H., 1927. Floating-Point Computation, 1927, Prentice-Hall, 1973.

[32]Hazewinkel, Michiel, ed., "Cosine theorem", Encyclopedia of Mathematics, Springer, 2001, ISBN 978 -1-55608-010-4

[33]Omaima N. A. AL-Allaf, Abdelfatah Aref Tamimi and Mohammad A. Alia, Face Recognition System Based on Different Artificial Neural Networks Models and Training Algorithms, International Journal of Advanced Computer Science and Application, Vol.4, Issue.6, pp:40-47,Jun 2013.

[34]Abdelfatah Tamimi, Omaima AL-Allaf and Mohammad Alia, Eigen Faces and Principle Component Analysis for Face Recognition Systems: A Comparative Study, International Journal of Computers & Technology (IJCT), Vol.14, N4., pp:5650-5660, 28Feb2015.