Advertisement

A Novel Modeling for Video Summarization Using Constraint Satisfaction Programming

  • Haykel Boukadida
  • Sid-Ahmed Berrani
  • Patrick Gros
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8888)

Abstract

This paper focuses on automatic video summarization. We propose a novel modeling for summary creation using constraint satisfaction programming (CSP). The proposed modeling aims to provide the summarization method with more flexibility. It allows users to easily modify the expected summary depending on their preferences or the video type. Using this new modeling, constraints become easier to formulate. Moreover, the CSP solver explores more efficiently the search space. It provides more quickly better solutions. Our model is evaluated and compared with an existing modeling on tennis videos.

Keywords

Video Content Global Constraint Video Summarization Shot Boundary Video Summary 
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.
    Over, P., Smeaton, A.F., Awad, G.: The TRECVid 2008 BBC rushes summarization evaluation. In: The 2nd ACM TRECVid Video Summarization Workshop (2008)Google Scholar
  2. 2.
    Berrani, S., Boukadida, H., Gros, P.: Constraint satisfaction programming for video summarization. In: IEEE Int. Symp. on Multimedia, USA (2013)Google Scholar
  3. 3.
    Longfei, Z., Yuanda, C., Gangyi, D., Yong, W.: A computable visual attention model for video skimming. In: IEEE Int. Symp. on Multimedia, USA (2008)Google Scholar
  4. 4.
    Evangelopoulos, G., Zlatintsi, A., Skoumas, G., Rapantzikos, K., Maragos, P., Potamianos, A., Avrithis, Y.: Video event detection and summarization using audio, visual and text saliency. In: Int. Conf. on Acoustics, Speech and Signal Processing, Taiwan (2009)Google Scholar
  5. 5.
    Cooper, M., Foote, J.: Summarizing video using non-negative similarity matrix factorization. In: IEEE Workshop on Multimedia Signal Processing, USA (2002)Google Scholar
  6. 6.
    Gong, Y., Liu, X.: Video summarization with minimal visual content redundancies. In: IEEE Int. Conf. on Image Processing, Greece (2001)Google Scholar
  7. 7.
    Ponceleon, D., Amir, A., Srinivasan, S., Syeda-Mahmood, T., Petkovic, D.: Cuevideo: automated multimedia indexing and retrieval. In: ACM Int. Conf. on Multimedia, USA (1999)Google Scholar
  8. 8.
    Smith, M.A., Kanade, T.: Video skimming for quick browsing based on audio and image characterization. In: IEEE Conf. on Computer Vision and Pattern Recognition (1997)Google Scholar
  9. 9.
    Pfeiffer, S., Lienhart, R., Fischer, S., Effelsberg, W.: Abstracting digital movies automatically. Journal of Visual Communication and Image Representation 3, 345–353 (1996)CrossRefGoogle Scholar
  10. 10.
    Marcus, A., Bernstein, M.S., Badar, O., Karger, D.R., Madden, S., Miller, R.C.: Twitinfo: aggregating and visualizing microblogs for event exploration. In: Conf. on Human Factors in Computing Systems, Canada (2011)Google Scholar
  11. 11.
    Shamma, D., Kennedy, L., Churchill, E.: Summarizing media through short-messaging services. In: ACM Conf. on Computer Supported Cooperative Work, USA (2010)Google Scholar
  12. 12.
    Allen, J.F.: Maintaining knowledge about temporal intervals. Communications of the ACM, 832–843 (1983)Google Scholar
  13. 13.
    Jussien, N., Rochart, G., Lorca, X., et al.: Choco: an open source java constraint programming library. In: Workshop on Open-Source Software for Integer and Constraint Programming, France (2008)Google Scholar
  14. 14.
    Truong, B.T., Venkatesh, S.: Video abstraction: A systematic review and classification. ACM Trans. on Multimedia Computing, Communications, and Applications (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Haykel Boukadida
    • 1
  • Sid-Ahmed Berrani
    • 1
  • Patrick Gros
    • 2
  1. 1.Orange Labs - France TelecomCesson-SévignéFrance
  2. 2.InriaRennesFrance

Personalised recommendations