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Video Annotation System Based on Categorizing and Keyword Labelling

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Database Systems for Advanced Applications (DASFAA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5463))

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Abstract

In this work, we demonstrate an automatic video annotation system which can provide users with the representative keywords for new videos. The system explores the hierarchical concept model and multiple feature model to improve the effectiveness of annotation, which consists of two components: a SVM classifier to ascertain the category; and a multiple feature model to label the keywords. We implement the demo system using the videos downloaded from YouTube. The results show the superiority of our approach.

This research was supported by NSFC under Grant No.60603045.

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References

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Author information

Authors and Affiliations

  1. Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA & School of EECS, Peking University, China

    Bin Cui, Bei Pan, Ying Wang & Ce Zhang

  2. School of ITEE, University of Queensland, Australia

    Heng Tao Shen

Authors
  1. Bin Cui
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  2. Bei Pan
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  3. Heng Tao Shen
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  4. Ying Wang
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  5. Ce Zhang
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Editor information

Editors and Affiliations

  1. School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, Brisbane, Australia

    Xiaofang Zhou  & Ke Deng  & 

  2. Tokyo Institute of Technology, Graduate School of Information Science and Engineering, 2-12-1 Oh-Okayama Meguro-ku, 152-8552, Tokyo, Japan

    Haruo Yokota

  3. CSIRO, Castray Esplanade, TAS 7000, Hobart, Australia

    Qing Liu

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© 2009 Springer-Verlag Berlin Heidelberg

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Cui, B., Pan, B., Shen, H.T., Wang, Y., Zhang, C. (2009). Video Annotation System Based on Categorizing and Keyword Labelling. In: Zhou, X., Yokota, H., Deng, K., Liu, Q. (eds) Database Systems for Advanced Applications. DASFAA 2009. Lecture Notes in Computer Science, vol 5463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00887-0_68

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  • DOI: https://doi.org/10.1007/978-3-642-00887-0_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00886-3

  • Online ISBN: 978-3-642-00887-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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