Skip to main content
Springer Nature Link
Log in

Enabling Effective User Interactions in Content-Based Image Retrieval

  • Conference paper
Information Retrieval Technology (AIRS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5839))

Included in the following conference series:

Abstract

This paper presents an interactive content-based image retrieval framework—uInteract, for delivering a novel four-factor user interaction model visually. The four-factor user interaction model is an interactive relevance feedback mechanism that we proposed, aiming to improve the interaction between users and the CBIR system and in turn users overall search experience. In this paper, we present how the framework is developed to deliver the four-factor user interaction model, and how the visual interface is designed to support user interaction activities. From our preliminary user evaluation result on the ease of use and usefulness of the proposed framework, we have learnt what the users like about the framework and the aspects we could improve in future studies. Whilst the framework is developed for our research purposes, we believe the functionalities could be adapted to any content-based image search framework.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Bates, M.J.: Where should the person stop and the information search interface start? Information Processing and Management 26(5), 575–591 (1990)

    Article  Google Scholar 

  2. Campbell, I.: Interactive evaluation of the ostensive model using a new test collection of images with multiple relevance assessments. Journal of Information Retrieval 2(1) (2000)

    Google Scholar 

  3. Deselaers, T., Keysers, D., Ney, H.: Fire – flexible image retrieval engine: Imageclef 2004 evaluation. In: Peters, C., Clough, P., Gonzalo, J., Jones, G.J.F., Kluck, M., Magnini, B. (eds.) CLEF 2004. LNCS, vol. 3491, pp. 688–698. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  4. Heesch, D., Rüger, S.: Performance boosting with three mouse clicks-relevance feedback for CBIR. In: Proceeding of the European Conference on IR Research 2003 (2003)

    Google Scholar 

  5. Hopfgartner, F., Urban, J., Villa, R., Jose, J.: Simulated testing of an adaptive multimedia information retrieval system. In: Proceeding of Content-Based Multimedia Indexing (CBMI), pp. 328–335 (2007)

    Google Scholar 

  6. Liu, H., Uren, V., Song, D., Rüger, S.: A four-factor user interaction model for content-based image retrieval. In: Proceeding of the 2nd international conference on the theory of information retrieval, ICTIR (2009)

    Google Scholar 

  7. Müller, H., Müller, W., Marchand-Maillet, S., Pun, T.: Strategies for positive and negative relevance feedback in image retrieval. In: Proceedings of the International Conference on Pattern Recognition (ICPR 2000), Barcelona, Spain, September 2000, vol. 1, pp. 1043–1046 (2000)

    Google Scholar 

  8. Pickering, M.J., Rüger, S.: Evaluation of key frame-based retrieval techniques for video. Computer Vision and Image Understanding 92(2-3), 217–235 (2003)

    Article  Google Scholar 

  9. Ruthven, I., Lalmas, M., van Rijsbergen, K.: Incorporating user search behaviour into relevance feedback. Journal of the American Society for Information Science and Technology 54(6), 528–548 (2003)

    Article  Google Scholar 

  10. Spink, A., Greisdorf, H., Bateman, J.: From highly relevant to not relevant: examining different regions of relevance. Information Processing Management 34(5), 599–621 (1998)

    Article  Google Scholar 

  11. Urban, J., Jose, J.M.: Ego: A personalized multimedia management and retrieval tool. International Journal of Intelligent Systems 21, 725–745 (2006)

    Article  MATH  Google Scholar 

  12. Urban, J., Jose, J.M., van Rijsbergen, K.: An adaptive technique for content-based image retrieval. Multimedia Tools and Applications 31, 1–28 (2006)

    Article  Google Scholar 

  13. White, R.W., Ruthven, I.: A study of interface support mechanisms for interactive information retrieval. Journal of the American Society for Information Science and Technology (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Knowledge Media Institute, The Open University, Milton Keynes, MK7 6AA, UK

    Haiming Liu, Srđan Zagorac, Victoria Uren & Stefan Rüger

  2. School of Computing, The Robert Gordon University, Aberdeen, AB25 1HG, UK

    Dawei Song

Authors
  1. Haiming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Srđan Zagorac
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victoria Uren
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dawei Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stefan Rüger
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, 790-784, Pohang, Korea

    Gary Geunbae Lee

  2. School of Computing, The Robert Gordon University, St Andrew Street, AB25 1HG, Aberdeen, UK

    Dawei Song

  3. Microsoft Reseach Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Chin-Yew Lin

  4. National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430, Tokyo, Japan

    Akiko Aizawa

  5. School of Literature, Shirayuri College, 1-25 Midorigaoka, Chofu-shi, 182-8525, Tokyo, Japan

    Kazuko Kuriyama

  6. Graduate School of Information Science and Technology, Hokkaido University, North 14 West 9, Kita-ku. Sapporo-shi, 060-0814, Hokkaido, Japan

    Masaharu Yoshioka

  7. Microsoft Research Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Tetsuya Sakai

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, H., Zagorac, S., Uren, V., Song, D., Rüger, S. (2009). Enabling Effective User Interactions in Content-Based Image Retrieval. In: Lee, G.G., et al. Information Retrieval Technology. AIRS 2009. Lecture Notes in Computer Science, vol 5839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04769-5_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04769-5_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04768-8

  • Online ISBN: 978-3-642-04769-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation