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Online Macro-segmentation of Television Streams

  • Gaël Manson
  • Xavier Naturel
  • Sid-Ahmed Berrani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5371)

Abstract

This demo presents a complete system that automatically structures TV streams on the fly. The objective is to precisely and automatically determine the start and the end of each broadcasted TV program. The extracted programs can then be stored in a database to be used in novel services such as TV-on-Demand. The system performs on-the-fly detection of inter-programs using a reference database of inter-programs, as well as an offline detection and classification of repeated sequences. This offline phase allows us to automatically detect inter-programs as repeated sequences. The macro-segmentation is performed using the online and the offline results of inter-program detection as well as metadata, when available, in order to label extracted programs. The demo shows results on large real TV streams.

References

  1. 1.
    Berrani, S.A., Lechat, P., Manson, G.: TV broadcast macro-segmentation: Metadata-based vs. content-based approaches. In: Proc. of the ACM Int. Conf. on Image and Video Retrieval, Amsterdam, The Netherlands (July 2007)Google Scholar
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    Berrani, S.A., Manson, G., Lechat, P.: A non-supervised approach for repeated sequence detection in tv broadcast streams. Signal Processing: Image Communication, special issue on Semantic Analysis for Interactive Multimedia Services 23(7), 525–537 (2008)Google Scholar
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    Manson, G., Berrani, S.A.: An inductive logic programming-based approach for tv stream segment classification. In: Proc. of the IEEE Int. Symp. on Multimedia, Berkeley, CA, USA (December 2008)Google Scholar
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    Lienhart, R., Kuhmunch, C., Effelsberg, W.: On the detection and recognition of television commercials. In: Proc. of the IEEE Int. Conf. on Multimedia Computing and Systems, Ottawa, Canada (June 1997)Google Scholar
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    Naturel, X., Gros, P.: A fast shot matching strategy for detecting duplicate sequences in a television stream. In: Proc. of the 2nd Int. Workshop on Computer Vision meets Databases, Baltimore, MD, USA (June 2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Gaël Manson
    • 1
  • Xavier Naturel
    • 1
  • Sid-Ahmed Berrani
    • 1
  1. 1.Orange Labs – France Telecom R&DCesson-SévignéFrance

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