Skip to main content

Large-Scale Cross-Media Retrieval of WikipediaMM Images with Textual and Visual Query Expansion

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 5706)

Abstract

In this paper, we present our approaches for the WikipediaMM task at ImageCLEF 2008. We first experimented with a text-based image retrieval approach with query expansion, where the extension terms were automatically selected from a knowledge base that was semi-automatically constructed from Wikipedia. Encouragingly, the experimental results rank in the first place among all submitted runs. We also implemented a content-based image retrieval approach with query-dependent visual concept detection. Then cross-media retrieval was successfully carried out by independently applying the two meta-search tools and then combining the results through a weighted summation of scores. Though not submitted, this approach outperforms our text-based and content-based approaches remarkably.

Keywords

  • Image retrieval
  • textual query expansion
  • query-dependent visual concept detection
  • cross-media re-ranking

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-642-04447-2_99
  • Chapter length: 8 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   189.00
Price excludes VAT (USA)
  • ISBN: 978-3-642-04447-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   239.00
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tian, Y.H., Huang, T.J., Gao, W.: Exploiting multi-context analysis in semantic image classification. J. Zhejiang Univ. SCI. 6A(11), 1268–1283 (2005)

    CrossRef  Google Scholar 

  2. Strube, M., Ponzetto, S.: WikiRelate! Computing semantic relatedness using Wikipedia. In: Proc. of National Conference on Artificial Intelligence (AAAI 2006), Boston, Mass, pp. 1419–1424 (2006)

    Google Scholar 

  3. Nakayama, K., Hara, T., Nishio, S.: A thesaurus construction method from large scale web dictionaries. In: Proc. of IEEE International Conference on Advanced Information Networking and Applications (AINA 2007), pp. 932–939 (2007)

    Google Scholar 

  4. Huang, C., Tian, Y.H., Zhou, Z., Ling, C.X., Huang, T.J.: Keyphrase extraction using Semantic Networks Structure Analysis. In: Proc. of the sixth IEEE Int’l. Conf. on Data Mining (ICDM 2006), pp. 275–284. IEEE press, Hong Kong (2006)

    CrossRef  Google Scholar 

  5. Lowe, D.: Object recognition from local scale-invariant feature. In: Proc. Int’l Conf. Computer Vision (ICCV 1999), pp. 1150–1157 (1999)

    Google Scholar 

  6. Lazebnik, S., Schmid, C., Ponce, J.: Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In: Proceedings of the IEEE CVPR 2006, pp. 2169–2178 (2006)

    Google Scholar 

  7. Hofmann, T.: Unsupervised learning by probabilistic latent semantic analysis. Machine Learning 41, 177–196 (2001)

    CrossRef  MATH  Google Scholar 

  8. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach Intell. 22(12), 1349–1380 (2000)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhou, Z., Tian, Y., Li, Y., Huang, T., Gao, W. (2009). Large-Scale Cross-Media Retrieval of WikipediaMM Images with Textual and Visual Query Expansion. In: , et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_99

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04447-2_99

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04446-5

  • Online ISBN: 978-3-642-04447-2

  • eBook Packages: Computer ScienceComputer Science (R0)