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Suspicious human activity detection in classroom examination

Publication Type : Conference Proceedings

Publisher : Advances in Intelligent Systems and Computing

Source : Advances in Intelligent Systems and Computing, Springer , Volume 412, p.99-108 (2016)

Url :

ISBN : 9789811002502

Keywords : Face detection, Haar casacade, Hand movement detection, Video analytics

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Computer Science

Year : 2016

Abstract : The proposed work aims in developing a system that analyze and detect the suspicious activity that are often occurring in a classroom environment. Video Analytics provides an optimal solution for this as it helps in pointing out an event and retrieves the relevant information from the video recorded. The system framework consists of three parts to monitor the student activity during examination. Firstly, the face region of the students is detected and monitored using Haar feature Extraction. Secondly, the hand contact detection is analyzed when two students exchange papers or any other foreign objects between them by grid formation. Thirdly, the hand signaling of the student using convex hull is recognized and the alert is given to the invigilator. The system is built using C/C++ and OpenCV library that shows the better performance in the real-time video frames. © Springer Science+Business Media Singapore 2016.

Cite this Research Publication : Dr. Senthil Kumar T. and Narmatha, G., “Suspicious human activity detection in classroom examination”, Advances in Intelligent Systems and Computing, vol. 412. Springer , pp. 99-108, 2016.

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