Split and Merge Based Story Segmentation in News Videos

Goyal, A., Punitha, P., Hopfgartner, F. and Jose, J. M. (2009) Split and Merge Based Story Segmentation in News Videos. In: ECIR'09: 31st European Conference on IR Research, Toulouse, France, 6-9 Apr 2009, pp. 766-770. ISBN 9783642009570 (doi: 10.1007/978-3-642-00958-7_82)

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.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Hopfgartner, Dr Frank and Goyal, Mr Anuj
• Authors: Goyal, A., Punitha, P., Hopfgartner, F., and Jose, J. M.
• College/School: College of Arts & Humanities > School of Humanities > Information Studies
• Publisher: Springer Verlag
• ISSN: 0302-9743
• ISBN: 9783642009570
• Copyright Holders: Copyright © 2009 Springer-Verlag Berlin Heidelberg
• First Published: First published in Advances in Information Retrieval: 766-770
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher