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Semantic Based Adaptive Movie Summarisation

  • Reede Ren
  • Hemant Misra
  • Joemon M. Jose
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5916)

Abstract

This paper proposes a framework for automatic video summarization by exploiting internal and external textual descriptions. The web knowledge base Wikipedia is used as a middle media layer, which bridges the gap between general user descriptions and exact film subtitles. Latent Dirichlet Allocation (LDA) detects as well as matches the distribution of content topics in Wikipedia items and movie subtitles. A saliency based summarization system then selects perceptually attractive segments from each content topic for summary composition. The evaluation collection consists of six English movies and a high topic coverage is shown over official trails from the Internet Movie Database.

Keywords

Content-based video summarisation latent Dirichlet allocation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Reede Ren
    • 1
  • Hemant Misra
    • 1
  • Joemon M. Jose
    • 1
  1. 1.Information Retrieval GroupUniversity of GlasgowGlasgowUK

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