A video grammar-based approach for TV news localization and intra-structure identification in TV streams

  • Authors:

  • Tarek Zlitni;Walid Mahdi;Hanène Ben-Abdallah

  • Affiliations:

  • MIRACL, Multimedia, Information Systems and Advanced Computing Laboratory, University of Sfax, Tunisia;MIRACL, Multimedia, Information Systems and Advanced Computing Laboratory, University of Sfax, Tunisia;MIRACL, Multimedia, Information Systems and Advanced Computing Laboratory, University of Sfax, Tunisia

  • Venue:
  • ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
  • Year:
  • 2011

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Abstract

The growing number of TV channels led to an expansion of the mass of video documents produced and broadcast on TV channels according to precise rules (e.g. consideration of the graphic charter, recurring of studios...). Thus, the use of a priori knowledge deduced from these rules contributes to the amelioration of the quality of segmentation and indexing of video documents. However, the effectiveness of automatic video segmentation works depends on video type. So, for a better quality of the segmentation, it is necessary to consider a priori knowledge concerning video types. In this context, this paper suggests an approach based on video grammar to identify programs in TV streams and deduce their internal structure. This approach attempts to automatically extract a priori knowledge to conceive the grammar descriptors. The study case of TV news programs is selected to validate the adopted approach since it is one of the most important types of multimedia content.