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Fast Structuring of Large Television Streams Using Program Guides

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Adaptive Multimedia Retrieval: User, Context, and Feedback (AMR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4398))

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Abstract

An original task of structuring and labeling large television streams is tackled in this paper. Emphasis is put on simple and efficient methods to detect precise boundaries of programs. These programs are further analysed and labeled with information coming from a standard television program guide using an improved Dynamic Time Warping algorithm (DTW) and a manually labeled reference video dataset. It is shown that the labeling process yields a very high accuracy and opens the way to many applications. We eventually indicate how the dependency to a manually labeled video dataset can be removed by providing an algorithm for a dynamic update of the reference video dataset.

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References

  1. EBU: Ets 300 231, television systems; specification of the domestic video programme delivery control system (pdc) (1993)

    Google Scholar 

  2. Lienhart, R., Kuhmunch, C., Effelsberg, W.: On the detection and recognition of television commercials. In: International Conference on Multimedia Computing and Systems, pp. 509–516 (1997), citeseer.ist.psu.edu/lienhart96detection.html

  3. Sadlier, D., et al.: Automatic tv advertisement detection from mpeg bitstream. Journal of the Patt. Rec. Society 35, 2–15 (2002)

    Google Scholar 

  4. McGee, T., Dimitrova, N.: Parsing tv program structures for identification and removal of non-story segments. In: SPIE Conf. on Storage and Retrieval for Image and Video Databases (1999)

    Google Scholar 

  5. Duygulu, P., Chen, M.-y., Hauptmann, A.: Comparison and combination of two novel commercial detection methods. In: ICME (2004)

    Google Scholar 

  6. Covell, M., Baluja, S., Fink, M.: Advertisement detection and replacement using acoustic and visual repetition. In: MMSP’06, IEEE 8th workshop on Multimedia Signal Procesing, Victoria, Canada, October 2006, IEEE Computer Society Press, Los Alamitos (2006)

    Google Scholar 

  7. Liang, L., et al.: Program segmentation for tv videos. In: ISCAS, IEEE International Symposium on Circuits and Systems, vol. 2, pp. 1549–1552. IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

  8. Naturel, X., Gros, P.: A fast shot matching strategy for detecting duplicate sequences in a television stream. In: CVDB’05, Baltimore (June 2005)

    Google Scholar 

  9. Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech and Signal Processing 26(1), 43–49 (1978)

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Stéphane Marchand-Maillet Eric Bruno Andreas Nürnberger Marcin Detyniecki

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© 2007 Springer Berlin Heidelberg

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Naturel, X., Gravier, G., Gros, P. (2007). Fast Structuring of Large Television Streams Using Program Guides. In: Marchand-Maillet, S., Bruno, E., Nürnberger, A., Detyniecki, M. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2006. Lecture Notes in Computer Science, vol 4398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71545-0_17

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  • DOI: https://doi.org/10.1007/978-3-540-71545-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71544-3

  • Online ISBN: 978-3-540-71545-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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