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Suspicious Human Activity Detection in Classroom Examination

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Book cover Computational Intelligence, Cyber Security and Computational Models

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 412))

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.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India

    T. Senthilkumar

  2. M.Tech (Computer Vision and Image Processing) Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India

    G. Narmatha

Authors
  1. T. Senthilkumar
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  2. G. Narmatha
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Corresponding author

Correspondence to T. Senthilkumar .

Editor information

Editors and Affiliations

  1. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Muthukrishnan Senthilkumar

  2. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Vijayalakshmi Ramasamy

  3. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Shina Sheen

  4. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    C. Veeramani

  5. Department of Mathematics, Ryerson University, TORONTO, Ontario, Canada

    Anthony Bonato

  6. Fac. Science&Technology, Deakin University, Burwood, Australia

    Lynn Batten

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Senthilkumar, T., Narmatha, G. (2016). Suspicious Human Activity Detection in Classroom Examination. In: Senthilkumar, M., Ramasamy, V., Sheen, S., Veeramani, C., Bonato, A., Batten, L. (eds) Computational Intelligence, Cyber Security and Computational Models. Advances in Intelligent Systems and Computing, vol 412. Springer, Singapore. https://doi.org/10.1007/978-981-10-0251-9_11

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  • DOI: https://doi.org/10.1007/978-981-10-0251-9_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0250-2

  • Online ISBN: 978-981-10-0251-9

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