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Automatic Visualization of Story Clusters in TV Series Summary

  • Conference paper
Advances in Multimedia Modeling (MMM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5916))

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Abstract

This paper describes a visualization method for showing clusters of video stories for the purpose of summarizing an episode of a TV series. Key frames from the video story segments are automatically extracted and clustered based on their visual similarity. Important keywords are then extracted from video subtitles to describe the semantic content of each story cluster in the form of tag clouds. The evaluation of the automatic processing has shown promising results, as the generated summaries are accurate and descriptive.

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Author information

Authors and Affiliations

  1. Faculty of Science and Technology, Queensland University of Technology, Brisbane, Australia

    Johannes Sasongko & Dian Tjondronegoro

Authors
  1. Johannes Sasongko
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  2. Dian Tjondronegoro
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Editor information

Editors and Affiliations

  1. University of Oldenburg, Germany

    Susanne Boll

  2. University of Texas at San Antonio,, TX, San Antonio, USA

    Qi Tian

  3. Microsoft Research Asia, Beijing, P.R. China

    Lei Zhang

  4. Southwest University, Beibei, Chongqing, China

    Zili Zhang

  5. School of Engineering and Information Technology, Deakin University, 221 Burwood Highway, Vic, 3125, Australia

    Yi-Ping Phoebe Chen

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Sasongko, J., Tjondronegoro, D. (2010). Automatic Visualization of Story Clusters in TV Series Summary. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_65

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  • DOI: https://doi.org/10.1007/978-3-642-11301-7_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11300-0

  • Online ISBN: 978-3-642-11301-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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