Split and Merge Based Story Segmentation in News Videos

  • Anuj Goyal
  • P. Punitha
  • Frank Hopfgartner
  • Joemon M. Jose
Conference paper

DOI: 10.1007/978-3-642-00958-7_82

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)
Cite this paper as:
Goyal A., Punitha P., Hopfgartner F., Jose J.M. (2009) Split and Merge Based Story Segmentation in News Videos. In: Boughanem M., Berrut C., Mothe J., Soule-Dupuy C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg

Abstract

Segmenting videos into smaller, semantically related segments which ease the access of the video data is a challenging open research. In this paper, we present a scheme for semantic story segmentation based on anchor person detection. The proposed model makes use of a split and merge mechanism to find story boundaries. The approach is based on visual features and text transcripts. The performance of the system was evaluated using TRECVid 2003 CNN and ABC videos. The results show that the system is in par with state-of-the-art classifier based systems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anuj Goyal
    • 1
  • P. Punitha
    • 1
  • Frank Hopfgartner
    • 1
  • Joemon M. Jose
    • 1
  1. 1.Department of Computing ScienceUniversity of GlasgowGlasgowUnited Kingdom

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