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Cognitive environment for pervasive learners

Publication Type : Journal Article

Thematic Areas : TIFAC-CORE in Cyber Security

Publisher : Communications in Computer and Information Science

Source : Communications in Computer and Information Science, vol. 191 CCIS, pp. 506-515, 2011.

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-80051563050&partnerID=40&md5=4d48813e70b571dfb7c4024a0b1718aa

ISBN : 9783642227134

Keywords : AdaBoost algorithm, Adaptive boosting, Algorithms, Binary features, Classroom teaching, Cognitive systems, Detection process, Eigen faces, Face detector, Face recognition, Feature extraction, Haar cascade, Haar features, Hand gesture, Head pose, Image sensing, Kalman filters, Lighting conditions, PCA, Principal component analysis, Principle component analysis, Recognition rates, Sensors, Teaching

Campus : Coimbatore

School : Centre for Cybersecurity Systems and Networks, School of Engineering

Center : TIFAC CORE in Cyber Security

Department : Computer Science, cyber Security

Year : 2011

Abstract : We present a novel approach for taking the ordinary classroom teaching to a new level, by creating a cognitive environment which includes the use of an image sensing device, number of client/student systems and a master/faculty system connected over a network. An automatic face detector and recognizer are activated on all the client systems for taking the attendance. The detection process is based on the adaboost algorithm, which is a cascade of binary features to rapidly locate and detect faces; recognition is achieved using principle component analysis. Hand gesture detection for students to raise doubts is achieved using adaboost algorithm. The system can also detect whether the students are asleep by extracting the eye region alone and applying principle component analysis to classify whether eyes are closed or open. Kalman filter is used to track the detected eye in consecutive frames. Experimental results show that our system is a viable approach and achieves good detection and recognition rates across wide range of head poses with different lighting conditions. © 2011 Springer-Verlag.

Cite this Research Publication : S. Sharma, Sreevathsan, R., Srikanth, M. V. V. N. S., Harshith, C., and Dr. Gireesh K. T., “Cognitive environment for pervasive learners”, Communications in Computer and Information Science, vol. 191 CCIS, pp. 506-515, 2011.

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