Advertisement

Video Retrieval Using an EDL-Based Timeline

  • José San Pedro
  • Nicolas Denis
  • Sergio Domínguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3522)

Abstract

In creating a new multimedia asset, specially a video, some decisions have to be made: a selection of the portions of the original footage that might be included, how to order them, how to crop each portion in order to reach the desired length and how to stitch all these pieces together. All these decisions constitute the core of the so called Editing Decision List, where all these actions are stored for the record. In this paper the authors show that the list of editing decisions can be used as the basis for indexing and retrieving videos from a database; more specifically, we show that a timeline created from the EDL is a valid and sufficient descriptor for identifying a video among a huge population, assuming a minimum duration. We demonstrate, as well, that this descriptor has a very good behavior in terms of robustness given different bit and frame rates, sizes and re-encoding processes. Indexing and retrieval using this descriptor is tested in a IPMP application for TV broadcasting.

Keywords

Time Stamp Video Retrieval Query Object Database Object Video Database 
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.
    del Bimbo, A.: Visual Information Retrieval. Morgan Kauffman Publishers, Inc., San Francisco (1999)Google Scholar
  2. 2.
    Jolion, J.M.: Feature Similarity. In: Principles of Visual Information Retrieval, Springer, Heidelberg (1999)Google Scholar
  3. 3.
    Rui, Y., Huang, T.S.: Relevance Feedback Techniques in Image Retrieval. In: Principles of Visual Information Retrieval, Springer, Heidelberg (1999)Google Scholar
  4. 4.
    Lienhart, R.: Comparison of Automatic Shot Boundary Detection Algorithms. In: Image and Video Processing VII, SPIE (1999)Google Scholar
  5. 5.
    Brown, L., Gruenwald, L.: Tree-Based Indexes for Image Data. Journal of Visual Communication and Image Representation 9, 300–313 (1998)CrossRefGoogle Scholar
  6. 6.
    Smith, M.A., Chen, T.: Image and Video Indexing and Retrieval. In: Handbook of Image and Video Processing, Academic Press, London (2000)Google Scholar
  7. 7.
    Boreczky, J.S., Rowe, L.A.: Comparison of Video Shot Boundary Detection Techniques. In: Storage and Retrieval for Still Image and Video Databases IV, SPIE (1996)Google Scholar
  8. 8.
    Y, S.: A new video segmentation method using variable interval frame differencing for digital video library applications. Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access (2003)Google Scholar
  9. 9.
    S, P., M, M., B, T.: Temporal video segmentation and classification of edit effects. Image And Vision Computing 21, 1097–1106 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • José San Pedro
    • 1
  • Nicolas Denis
    • 2
  • Sergio Domínguez
    • 1
  1. 1.UPM DISAMUniversidad Politécnica de Madrid 
  2. 2.Omnividea MultimediaMadrid

Personalised recommendations