Advertisement

Improvement of Commercial Boundary Detection Using Audiovisual Features

  • Jun-Cheng Chen
  • Jen-Hao Yeh
  • Wei-Ta Chu
  • Jin-Hau Kuo
  • Ja-Ling Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3767)

Abstract

Detection of commercials in TV videos is difficult because the diversity of them puts up a high barrier to construct an appropriate model. In this work, we try to deal with this problem through a top-down approach. We take account of the domain knowledge of commercial production and extract features that describe the characteristics of commercials. According to the clues from speech-music discrimination, video scene detection, and caption detection, a multi-modal commercial detection scheme is proposed. Experimental results show good performance of the proposed scheme on detecting commercials in news and talk show programs.

Keywords

Video Scene News Program Caption Ratio Caption Text Boundary Refinement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lienhart, R., Kuhmünch, C., Effelsberg, W.: On the Detection and Recognition of Television Commercials. In: Proceedings of IEEE International Conference Multimedia Computing and Systems, pp. 509–516 (1997)Google Scholar
  2. 2.
    Sundaram, H., Chang, S.-F.: Computable Scenes and Structures in Films. IEEE Transactions on Multimedia 4(4), 482–491 (2002)CrossRefGoogle Scholar
  3. 3.
    Duygulu, P., Chen, M.-Y., Hauptmann, A.: Comparison and Combination of Two Novel Commercial Detection Methods. In: Proceedings of IEEE International Conference on Multimedia and Expo, vol. 2, pp. 1267–1270 (2004)Google Scholar
  4. 4.
    Sánchez, J.M., Binefa, X., Vitrià, J., Radeva, P.: Local Color analysis for Scene Break Detection Applied to TV Commercials Recognition. In: Huijsmans, D.P., Smeulders, A.W.M. (eds.) VISUAL 1999. LNCS, vol. 1614, pp. 237–244. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  5. 5.
    Satterwhite, B., Marques, O.: Automatic detection of TV commercials. IEEE Potentials 23(2), 9–12 (2004)CrossRefGoogle Scholar
  6. 6.
    Albiol, A., Ch, M.J., Albiol, F.A., Torres, L.: Detection of TV commercials. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 3, pp. 541–544 (2004)Google Scholar
  7. 7.
    Liu, T.-Y., Qin, T., Zhang, H.-J.: Time-constraint boost for TV commercials detection. In: IEEE International Conference on Image Processing, vol. 3, pp. 1617–1620 (2004)Google Scholar
  8. 8.
    Panagiotakis, C., Tziritas, G.: A speech/music discriminator based on RMS and Zerocrossings. IEEE Transactions on Multimedia 7(1), 155–166 (2005)CrossRefGoogle Scholar
  9. 9.
    Tsao, C.-F., Chen, Y.-H., Kuo, J.-H., Lin, C.-W., Wu, J.-L.: Automatic Video Caption Detection and Extraction in the DCT Compression Domain. In: Accepted by Visual Communications and Image Processing (2005)Google Scholar
  10. 10.
    Yeh, J.-H., Chen, J.-C., Kuo, J.-H., Wu, J.-L.: TV Commercial Detection in News Program Videos. Accepted by IEEE International Symposium on Circuits and Systems, 4594–4597 (2005)Google Scholar
  11. 11.
    Enforcement Rules of the Radio and Television Act, article 34, http://www.gio.gov.tw/taiwan-website/1-about_us/6-laws/ra8.htm

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jun-Cheng Chen
    • 1
  • Jen-Hao Yeh
    • 1
  • Wei-Ta Chu
    • 1
  • Jin-Hau Kuo
    • 1
  • Ja-Ling Wu
    • 1
    • 2
  1. 1.Department of Computer Science and Information EngineeringNational Taiwan University 
  2. 2.Graduate Institute of Networking and MultimediaNational Taiwan UniversityTaipeiTaiwan , ROC

Personalised recommendations