• DocumentCode
    2323672
  • Title

    News Story Segmentation in Multiple Modalities

  • Author

    Poulisse, Gert-Jan ; Moens, Marie-Francine ; Dekens, Tomas

  • Author_Institution
    Dept. of Comput. Sci., Katholieke Univ. Leuven, Leuven
  • fYear
    2009
  • fDate
    3-5 June 2009
  • Firstpage
    25
  • Lastpage
    32
  • Abstract
    In this paper, we describe an approach to segmenting news video based on the perceived shift in content using features spanning multiple modalities.We investigate a number of multimedia features, which serve as potential indicators of a change in story in order to determine which are the most effective. The efficacy of our approach is demonstrated by the performance of our prototype, where a number of feature combinations demonstrate an up to 18% improvement in Window Diff score above that of other state of the art story segmenters. In our investigation, there was no, one, clearly superior feature, rather the best segmentation results occurred when there was synergy between multiple features.
  • Keywords
    feature extraction; image segmentation; multimedia computing; video signal processing; art story segmenter; feature spanning multiple modality; multimedia feature; news video story segmentation; video signal processing; Broadcasting; Detectors; Entropy; Error analysis; Gunshot detection systems; Image segmentation; Indexing; Prototypes; Speech; Testing; feature extraction; story detection; video segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Content-Based Multimedia Indexing, 2009. CBMI '09. Seventh International Workshop on
  • Conference_Location
    Chania
  • Print_ISBN
    978-1-4244-4265-2
  • Electronic_ISBN
    978-0-7695-3662-0
  • Type

    conf

  • DOI
    10.1109/CBMI.2009.27
  • Filename
    5137811