Skip to main content

Three Interfaces for Content-Based Access to Image Collections

  • Conference paper
Book cover Image and Video Retrieval (CIVR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3115))

Included in the following conference series:

Abstract

This paper describes interfaces for a suite of three recently developed techniques to facilitate content-based access to large image and video repositories. Two of these techniques involve content-based retrieval while the third technique is centered around a new browsing structure and forms a useful complement to the traditional query-by-example paradigm. Each technique is associated with its own user interface and allows for a different set of user interactions. The user can move between interfaces whilst executing a particular search and thus may combine the particular strengths of the different techniques. We illustrate each of the techniques using topics from the TRECVID 2003 contest.

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. Aggarwal, G., Ashwin, T.V., Ghosal, S.: An image retrieval system with automatic query modification. IEEE Transactions on multimedia 4(2), 201–213 (2002)

    Article  Google Scholar 

  2. Campbell, I.: The ostensive model of developing information-needs. PhD thesis, University of Glasgow (2000)

    Google Scholar 

  3. Flickner, M., Sawhney, H., Niblack, W., Ashley, Q.H.J., Dom, B., Gorkani, M., Hafner, J., Lee, D., Petkovic, D., Steele, D., Yanker, P.: Query by image and video content: the QBIC system. IEEE Computer 9, 23–32 (1995)

    Google Scholar 

  4. Heesch, D.C., Pickering, M., Yavlinsky, A., Rüger, S.: Video retrieval within a browsing framework using keyframes. In: Proceedings of TRECVID 2003, NIST, Gaithersburg, MD (November 2003) (2004)

    Google Scholar 

  5. Heesch, D.C., Rüger, S.: Performance boosting with three mouse clicks — Relevance feedback for CBIR. In: Proceedings of the European Conference on IR Research 2003. LNCS, Springer, Heidelberg (2003)

    Google Scholar 

  6. Heesch, D.C., Rüger, S.: NNk networks for content based image retrieval. In: McDonald, S., Tait, J.I. (eds.) ECIR 2004. LNCS, vol. 2997, pp. 253–266. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Heesch, D.C., Yavlinsky, A., Rüger, S.: Performance comparison between different similarity models for CBIR with relevance feedback. In: Bakker, E.M., Lew, M., Huang, T.S., Sebe, N., Zhou, X.S. (eds.) CIVR 2003. LNCS, vol. 2728, Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  8. Mainzer, K.: Computerphilosophie. Junius Verlag (2003)

    Google Scholar 

  9. Müller, H., Müller, W., Squire, D.M., Marchand-Maillet, M.S., Pun, T.: Strategies for positive and negative relevance feedback in image retrieval. In: Proceedings of the 15th International Conference on Pattern Recognition (ICPR 2000), IEEE, Barcelona (2000)

    Google Scholar 

  10. Rui, T.S., Huang, T.S., Ortega, M., Mehrota, S.: Mehrota. Relevance feedback: a power tool for interactive content-based image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 123–131 (1998)

    Google Scholar 

  11. Santini, S., Gupta, A., Jain, R.: Emergent semantics through interaction in image databases. IEEE transactions on knowledge and data engineering 13(3), 337–351 (2001)

    Article  Google Scholar 

  12. Tian, Q., Moghaddam, B., Huang, T.S.: Display optimization for image browsing. In: International Workshop on Multimedia Databases and Image Communications (2001)

    Google Scholar 

  13. Torres, R.S., Silva, C.G., Medeiros, C.B., Rocha, H.V.: Visual structures for image browsing. In: Conference on Information Knowledge Management (CIKM 2003) (2003)

    Google Scholar 

  14. Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 393, 440–442 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Heesch, D., Rüger, S. (2004). Three Interfaces for Content-Based Access to Image Collections. In: Enser, P., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds) Image and Video Retrieval. CIVR 2004. Lecture Notes in Computer Science, vol 3115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27814-6_58

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-27814-6_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22539-3

  • Online ISBN: 978-3-540-27814-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics