Multimedia Tools and Applications

, Volume 75, Issue 10, pp 5645–5672 | Cite as

Automatic topics segmentation for TV news video using prior knowledge

Article

Abstract

TV streams represent a principal source of multimedia information. The goal of the proposed approach is to enable a better exploitation of this source of video by multimedia services (i.e., TV-On-Demand, catch-up TV), social community, and video-sharing platforms (Vimeo, Youtube, Facebook …). In this work, we present an automatic structuring approach of TV news. The originality of the approach is the use of the contextual and operational characteristics as prior knowledge. This knowledge is modeled as video grammar which governs the structuring of TV stream content. This structuring is carried out on two levels. The first level identifies news programs in TV stream. The second level aims to identify the internal structure of the identified news programs. At this level, we opt to treat the case of TV news programs due to the large audience because of pertinent information within. Comparison experiments to similar works have been carried out on the TRECVID 2003 database. We show significant improvements to TV news structuring exceed 90 %.

Keywords

TV stream structuring Video grammar TV news segmentation Content-based video indexing Automatic topics detection 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Higher Institute of Information Technology and MultimediaUniversity of SfaxSfaxTunisia
  2. 2.College of Computers and Information TechnologyTaif University, KSATaifSaudi Arabia
  3. 3.MIRACL LaboratorySfaxTunisia

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