Chapter

Advances in Information Retrieval

Volume 5478 of the series Lecture Notes in Computer Science pp 766-770

Split and Merge Based Story Segmentation in News Videos

  • Anuj GoyalAffiliated withDepartment of Computing Science, University of Glasgow
  • , P. PunithaAffiliated withDepartment of Computing Science, University of Glasgow
  • , Frank HopfgartnerAffiliated withDepartment of Computing Science, University of Glasgow
  • , Joemon M. JoseAffiliated withDepartment of Computing Science, University of Glasgow

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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.