Collaborative Video Scene Annotation Based on Tag Cloud

  • Daisuke Yamamoto
  • Tomoki Masuda
  • Shigeki Ohira
  • Katashi Nagao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5353)


In this paper, we propose a video scene annotation method based on tag clouds. First, user comments associated with a video are collected from existing video sharing services. Next, a tag cloud is generated from these user comments. The tag cloud is displayed on the video window of the Web browser. When users click on a tag included in the tag cloud while watching the video, the tag gets associated with the time point of the video. Users can share the information on the tags that have already been clicked. We confirmed that the coverage of annotations generated by this method is higher than that of the existing methods, and users are motivated to add tags by using tag-sharing and tag-cloud methods. This method assists in establishing highly accurate advanced video applications.


Collaborative Tagging Video Annotation Tag-cloud Web Service 


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  1. 1.
    Ben-Ezra, M., Nayar, S.K.: Motion-based motion deblurring. IEEE Trans. on Pattern analysis and machine intelligence 26(6), 689–698 (2004)CrossRefGoogle Scholar
  2. 2.
    Davis, M.: Media Streams: an iconic visual language for video annotation. In: Proc. of the IEEE Symp. on Visual Language, pp. 196–202 (1993)Google Scholar
  3. 3.
    Masuda, T., Yamamoto, D., Ohira, S., Nagao, K.: Video scene retrieval using online video annotation. In: Satoh, K., Inokuchi, A., Nagao, K., Kawamura, T. (eds.) JSAI 2007. LNCS, vol. 4914, pp. 255–268. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. 4.
    Matsumoto, Y., et al.: Japanese Morphological Analysis System ChaSen version 2.2.1 (2000),
  5. 5.
    Nagao, K., Ohira, S., Yoneoka, M.: Annotation-based multimedia summarization and translation. In: Proc. of the 19th Int’l Conf. on Computational Linguistics, pp. 702–708 (2002)Google Scholar
  6. 6.
    Nagao, K., Shirai, Y., Squire, K.: Semantic annotation and transcoding: Making Web content more accessible. IEEE MultiMedia 8(2), 69–81 (2001)CrossRefGoogle Scholar
  7. 7.
    Parker, C., Pfeiffer, S.: Video blogging: Content to the max. IEEE MultiMedia 12(2), 4–8 (2005)CrossRefGoogle Scholar
  8. 8.
    Rivadeneira, A.W., Gruen, D.M., Muller, M.J., Millen, D.R.: Getting our head in the clouds: toward evaluation studies of tagclouds. In: Proc. of the ACM CHI Conference on Human factors in Computing Systems, pp. 995–998 (2007)Google Scholar
  9. 9.
    Smith, J.R., Lugeon, B.: A visual annotation tool for multimedia content description. In: Proc. of the SPIE Photonics East (2000)Google Scholar
  10. 10.
    Volkmer, T., Smith, J.R., Natsev, A.P.: A web-based system for collaborative annotation of large image and video collections: An evalusation and user study. In: Proc. of the 13th ACM Int’l Conf. on Multimedia, pp. 892–901 (2005)Google Scholar
  11. 11.
    Ahn, L., Dabbish, L.: Labeling images with a computer game. In: Proc. of the ACM CHI Conf. on Human Factors in Computing Systems, pp. 24–29 (2004)Google Scholar
  12. 12.
    Wactlar, H.D., et al.: Intelligent access to digital video: Informedia project. IEEE Computer 29(5), 140–151 (1996)CrossRefGoogle Scholar
  13. 13.
    Yamamoto, D., Masuda, T., Ohira, S., Nagao, K.: Video scene annotation based on web social activities. IEEE MultiMedia 15(3), 22–32 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Daisuke Yamamoto
    • 1
    • 2
  • Tomoki Masuda
    • 1
  • Shigeki Ohira
    • 1
  • Katashi Nagao
    • 1
  1. 1.Nagoya University, Furo-cho, Chikusa-kuNagoyaJapan
  2. 2.Nagoya Institute of Technology, Gokiso-cho, Showa-kuNagoyaJapan

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