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Large-scale Text-based Video Classification using Contextual Features

Author

Listed:
  • Zein Al Abidin Ibrahim

    (Lebanese University-Faculty of Sciences)

  • Siba Haidar

    (Lebanese University-Faculty of Sciences)

  • Ihab Sbeity

    (Lebanese University-Faculty of Sciences)

Abstract

The production of video has increased and expanded dramatically. There is a need to reach accurate video classification. In our work, we use deep learning as a mean to accelerate the video retrieval task by classifying them into categories. We classify a video depending on the text extracted from it. We trained our model using fastText, a library for efficient text classification and representation learning, and tested our model on 15000 videos. Experimental results show that our approach is efficient and has good performance. Our technique can be used on huge datasets. It produces a model that can be used to classify any video into a specific category very quickly.

Suggested Citation

  • Zein Al Abidin Ibrahim & Siba Haidar & Ihab Sbeity, 2019. "Large-scale Text-based Video Classification using Contextual Features," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 3(2), March.
    • Handle: RePEc:epw:ejece0:v:3:y:2019:i:2:id:19068
    DOI: 10.24018/ejece.2019.3.2.68
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