Skip to main content

Video Clip Matching Using MPEG-7 Descriptors and Edit Distance

  • Conference paper
Image and Video Retrieval (CIVR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4071))

Included in the following conference series:

Abstract

Video databases require that clips are represented in a compact and discriminative way, in order to perform efficient matching and retrieval of documents of interest. We present a method to obtain a video representation suitable for this task, and show how to use this representation in a matching scheme. In contrast with existing works, the proposed approach is entirely based on features and descriptors taken from the well established MPEG-7 standard. Different clips are compared using an edit distance, in order to obtain high similarity between videos that differ for some subsequences, but are essentially related to the same content. Experimental validation is performed using a prototype application that retrieves TV commercials recorded from different TV sources in real time. Results show excellent performances both in terms of accuracy, and in terms of computational performances.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adjeroh, D.A., King, I., Lee, M.C.: A distance measure for video sequences. Computer Vision and Image Understanding (CVIU) 75(1) (1999)

    Google Scholar 

  2. DeMenthon, D., Doermann, D.: Video retrieval using spatio-temporal descriptors. In: Proc. of ACM Multimedia (2003)

    Google Scholar 

  3. Duygulu, P., Chen, M.-Y., Hauptmann, A.: Comparison and combination of two novel commercial detection methods. In: Proc. of Int. Conf. of Multimedia and Expo (CME) (2004)

    Google Scholar 

  4. Hampapur, A., Bolle, R.: Feature based indexing for media tracking. In: Proc. of Int. Conf. on Multimedia and Expo (ICME) (2000)

    Google Scholar 

  5. Kim, Y.-T., Chua, T.-S.: Retrieval of news video using video sequence matching. In: Proc. of Multimedia Modelling Conference (2005)

    Google Scholar 

  6. Hoad, T.C., Zobel, J.: Fast video matching with signature alignment. In: Proc. of Workshop on Multimedia Information Retrieval (MIR) (2003)

    Google Scholar 

  7. Kasutani, E., Yamada, A.: The MPEG-7 Color Layout Descriptor: a Compact Image feature Description for High-Speed Image/Video Segment Retrieval. In: IEEE Proc. of International Conference on Image Processing (ICIP 2001), October 2001, vol. I, pp. 674–677 (2001)

    Google Scholar 

  8. Kasutani, E., Yamada, A.: An Adaptive Feature Comparison Method for Real-time Video Identification. In: IEEE Proc. of International Conference on Image Processing (ICIP 2003), September, vol. II, pp. 5–8 (2003)

    Google Scholar 

  9. Li, Y., Jin, J.S., Zhou, X.: Matching commercial clips from TV streams using a unique, robust and compact signature. In: Proc. of Digital Image Computing: Techniques and Applications (DICTA) (2005)

    Google Scholar 

  10. Lienhart, C.K.R., Effelsberg, W.: On the detection and recognition of television commercials. In: Proc. of Int. Conf. on Multimedia Computing and Systems (ICMCS) (1997)

    Google Scholar 

  11. Manjunath, B.S., Ohm, J.-R., Vasudevan, V.V.: Color and Texture Descriptors. IEEE Transactions on Circuits and Systems for Video Technology 11(6) (June 2001)

    Google Scholar 

  12. Mohan, R.: Video sequence matching. In: Proc. of Int. Conf. on Audio, Speech and Signal Processing (ICASSP) (1998)

    Google Scholar 

  13. Naturel, X., Gros, P.: A fast shot matching strategy for detecting duplicate sequences in a television stream. In: Proc. of Int. Workshop on Computer Vision meets Databases (CVDB) (2005)

    Google Scholar 

  14. Navarro, G.: A guided tour to approximate string matching. ACM Computing Surveys 33 (2001)

    Google Scholar 

  15. Oostveen, J., Kalker, T., Haitsma, J.: Feature extraction and a database strategy for video fingerprinting. In: Chang, S.-K., Chen, Z., Lee, S.-Y. (eds.) VISUAL 2002. LNCS, vol. 2314, p. 117. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  16. Pua, K.M., Gauch, J.M., Gauch, S.E., Miadowicz, J.Z.: Real time repeated video sequence identification. Computer Vision and Image Understanding (CVIU) 93(3) (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bertini, M., Del Bimbo, A., Nunziati, W. (2006). Video Clip Matching Using MPEG-7 Descriptors and Edit Distance. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_14

Download citation

  • DOI: https://doi.org/10.1007/11788034_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36018-6

  • Online ISBN: 978-3-540-36019-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics