Advertisement

Summarization and Presentation of Real-Life Events Using Community-Contributed Content

  • Manfred Del Fabro
  • Laszlo Böszörmenyi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)

Abstract

We present an algorithm for the summarization of social events with community-contributed content from Flickr and YouTube. A clustering algorithm groups content related to the searched event. Date information, GPS coordinates, user ratings and visual features are used to select relevant photos and videos. The composed event summaries are presented with our video browser.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chatzichristofis, S.A., Boutalis, Y.S.: CEDD: Color and Edge Directivity Descriptor: A Compact Descriptor for Image Indexing and Retrieval. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds.) ICVS 2008. LNCS, vol. 5008, pp. 312–322. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  2. 2.
    Sinha, P., Mehrotra, S., Jain, R.: Summarization of personal photologs using multidimensional content and context. In: Proc. of the 1st ACM International Conference on Multimedia Retrieval, pp. 4:1–4:8. ACM, New York (2011)Google Scholar
  3. 3.
    Zamir, O., Etzioni, O.: Web document clustering: a feasibility demonstration. In: Proc. of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 46–54. ACM, New York (1998)Google Scholar
  4. 4.
    Del Fabro, M., Schoeffmann, K., Böszörmenyi, L.: Instant Video Browsing: A Tool for Fast Non-sequential Hierarchical Video Browsing. In: Leitner, G., Hitz, M., Holzinger, A. (eds.) USAB 2010. LNCS, vol. 6389, pp. 443–446. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Manfred Del Fabro
    • 1
  • Laszlo Böszörmenyi
    • 1
  1. 1.Institute of Information TechnologyKlagenfurt UniversityAustria

Personalised recommendations