Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Retrieval Method for Video Content in Different Format Based on Spatiotemporal Features

  • Conference paper
Advances in Information Retrieval (ECIR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4425))

Included in the following conference series:

  • 2061 Accesses

Abstract

In this paper a robust video content retrieval method based on spatiotemporal features is proposed. To date, most video retrieval methods are using the character of video key frames. This kind of frame based methods is not robust enough for different video format. With our method, the temporal variation of visual information is presented using spatiotemporal slice. Then the DCT is used to extract feature of slice. With this kind of feature, a robust video content retrieval algorithm is developed. The experiment results show that the proposed feature is robust for variant video format.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Hua, X.-S., Chen, X., Zhang, H.-J.: Robust Video Signature Based on Ordinal Measure. In: International Conference on Image Processing, pp. 685–688 (2004)

    Google Scholar 

  2. Hampapur, A., Hyun, K.-H., Bolle, R.: Comparison of Sequence Matching Techniques for Video Copy Detection. In: Proc. Storage and Retrieval for Media Databases, Jan. 2002, pp. 194–201 (2002)

    Google Scholar 

  3. Kim, C., Vasudev, B.: Spatiotemporal Sequence Matching for Efficient Video Copy Detection. IEEE Transactions on Circuits and Systems for Video Technology 15(1), 127–132 (2005)

    Article  Google Scholar 

  4. Ngo, C.-W., Pong, T.-C., Zhang, H.-J.: On Clustering and Retrieval of Video Shots through Temporal Slices Analysis. IEEE Transactions on Multimedia 4(4), 446–458 (2002)

    Article  Google Scholar 

  5. Peng., S.L., Medioni, G.: Interpretation of image sequences by spatio-temporal analysis. In: Workshop on Visual Motion, March 1989, pp. 344–351 (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Giambattista Amati Claudio Carpineto Giovanni Romano

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Pan, X., Li, J., Zhang, Y., Tang, S., Cao, J. (2007). Retrieval Method for Video Content in Different Format Based on Spatiotemporal Features. In: Amati, G., Carpineto, C., Romano, G. (eds) Advances in Information Retrieval. ECIR 2007. Lecture Notes in Computer Science, vol 4425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71496-5_79

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-71496-5_79

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71494-1

  • Online ISBN: 978-3-540-71496-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics