Split and Merge Based Story Segmentation in News Videos

Authors:
Anuj Goyal;P. Punitha;Frank Hopfgartner;Joemon M. Jose
Affiliations:
Department of Computing Science, University of Glasgow, Glasgow, United Kingdom;Department of Computing Science, University of Glasgow, Glasgow, United Kingdom;Department of Computing Science, University of Glasgow, Glasgow, United Kingdom;Department of Computing Science, University of Glasgow, Glasgow, United Kingdom
Venue:
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Year:
2009

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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.