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Violence Video Classification Performance Using Deep Neural Networks

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Recent Advances on Soft Computing and Data Mining (SCDM 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 700))

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Abstract

Violence is autonomous, the contents that one would not let children to see in movies or web videos. This is a challenging problem due to strong content variations among the positive instances. To solve this problem, implementation of deep neural network to classify the violence content in videos is proposed. Currently, deep neural network has shown its efficiency in natural language processing, fraud detection, social media, text classification, image classification. Regardless of the conventional methods applied to overcome this issue, but these techniques seem insufficiently accurate and does not adopt well to certain webs or user needs. Therefore, the purpose of this study is to assess the classification performances on violence video using Deep Neural Network (DNN). Hence, in this paper different architectures of hidden layers and hidden nodes in DNN have been implemented using the try-error method and equation based method, to examine the effect of the number of hidden layers and hidden nodes to the classification performance. From the results, it indicates 53% accuracy rate for try and error approach, meanwhile for equation based approach it indicates 51% accuracy rate.

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Acknowledgements

This research funded by Ministry of Higher Education (MOHE) under the Fundamental Research Grant Scheme (FRGS)—Vot. No. 1608. Besides, partially supported by Office for Research, Innovation, Commercialization and Consultancy Management (ORICC), UTHM.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Ashikin Ali & Norhalina Senan

Authors
  1. Ashikin Ali
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  2. Norhalina Senan
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Corresponding author

Correspondence to Norhalina Senan .

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Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Nazri Mohd Nawi

  4. School of Information Technology, Deakin University, Geelong, Victoria, Australia

    Jemal H. Abawajy

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Ali, A., Senan, N. (2018). Violence Video Classification Performance Using Deep Neural Networks. In: Ghazali, R., Deris, M., Nawi, N., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2018. Advances in Intelligent Systems and Computing, vol 700. Springer, Cham. https://doi.org/10.1007/978-3-319-72550-5_22

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  • DOI: https://doi.org/10.1007/978-3-319-72550-5_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72549-9

  • Online ISBN: 978-3-319-72550-5

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