• DocumentCode
    3225246
  • Title

    Television Stream Structuring with Program Guides

  • Author

    Poli, Jean Philippe ; Carrive, Jean

  • Author_Institution
    LSIS, Univ. Paul Cezzane, Marseille
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    329
  • Lastpage
    334
  • Abstract
    We propose in this paper an original approach to the TV stream structuring problem. The goal of our work is to automatically break the TV stream into telecasts and advertisings and to label each telecast with its genre. One can think the TV stream structuring problem can be solved by an alignment of the program guide on the stream. But our study shows that, in average, only 25% of the telecasts per day are presented in the program guide. Hence, our method consists in improving statistically these program guides in order to reduce the TV stream structuring problem to a simple alignment problem. The improvement consists in adding the missing telecasts. We present an original system that lays on the modeling of past TV schedules by a contextual hidden Markov model and a regression tree. Interesting results are presented at the end of the paper
  • Keywords
    advertising; hidden Markov models; regression analysis; television broadcasting; trees (mathematics); video streaming; TV stream; advertisings; hidden Markov model; program guides; regression tree; telecasts; television stream structuring; Advertising; Computational efficiency; Feature extraction; Hidden Markov models; Indexing; Large scale integration; Regression tree analysis; Streaming media; TV broadcasting; Weather forecasting; Contextual Hidden Markov Model; Regression Trees; Television Stream Structuring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia, 2006. ISM'06. Eighth IEEE International Symposium on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    0-7695-2746-9
  • Type

    conf

  • DOI
    10.1109/ISM.2006.148
  • Filename
    4061185