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Boosting Cross-Media Retrieval by Learning with Positive and Negative Examples

  • Yueting Zhuang
  • Yi Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4352)

Abstract

Content-based cross-media retrieval is a new category of retrieval methods by which the modality of query examples and the returned results need not to be the same, for example, users may query images by an example of audio and vice versa. Multimedia Document (MMD) is a set of media objects that are of different modalities but carry the same semantics. In this paper, a graph based approach is proposed to achieve the content-based cross-media retrieval and MMD retrieval. Positive and negative examples of relevance feedback are used differently to boost the retrieval performance and experiments show that the proposed methods are very effective.

Keywords

Content-based Cross-media Retrieval Multimedia Document Relevance Feedback 

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References

  1. 1.
    Zhang, H.J., Zhong, D.: Schema for visual feature based image retrieval. In: Proceedings of Storage and Retrieval for Image and Video Database, USA, pp. 36–46 (1995)Google Scholar
  2. 2.
    Feng, H., Shi, R., Chua, T.S.: A bootstrapping framework for annotating and retrieving WWW images. In: Proc. of the ACM Int. Conf. on Multimedia, pp. 960–967 (2004)Google Scholar
  3. 3.
    He, X., Ma, W.Y., Zhang, H.J.: Learning an Image Manifold for Retrieval. In: ACM Multimedia Conference, New York (2004)Google Scholar
  4. 4.
    Jingrui, H., Mingjing, L., Hong-Jiang, Z., Hanghang, T., Changshui, Z.: Manifold-Ranking Based Image Retrieval. In: ACM Multimedia Conference, New York (2004)Google Scholar
  5. 5.
    Maddage, N.C., Xu., C., Kankanhalli, M.S., Shao, X.: Content-based Music Structure Analysis with Applications to Music Semantics Understanding. In: ACM Multimedia Conference, New York (2004)Google Scholar
  6. 6.
    Guo, G., Li, S.Z.: Content-based audio classification and retrieval by support vector machines. IEEE Transactions on Neural Networks 14(1), 209–215 (2003)CrossRefGoogle Scholar
  7. 7.
    Wold, E., Blum, T., Keislar, D., Wheaton, J.: Content-based classification, search and retrieval of audio. IEEE Multimedia Mag. 3, 27–36 (1996)CrossRefGoogle Scholar
  8. 8.
    Wu, M.Y., Chiu, C.Y., Chao, S.P., Yanga, S.N., Lin, H.C.: Content-Based Retrieval for Human Motion Data. In: 16th IPPR Conference on Computer Vision, Graphics and Image Processing (CVGIP 2003) (2003)Google Scholar
  9. 9.
    Müller, M., Röder, T., Clausen, M..: Efficient Content-Based Retrival of Motion Capture Data. In: Proceedings of ACM SIGGRAPH 2005 (2005)Google Scholar
  10. 10.
    Smoliar, S.W., Zhang, H.: Content based video indexing and retrieval, Multimedia. IEEE 1(2), 62–72 (1994)Google Scholar
  11. 11.
    Fan, J., Elmagarmid, A.K., Zhu, X., Aref, W.G., Wu., L.: ClassView: hierarchical video shot classification, indexing, and accessing, Multimedia. IEEE Transactions on 6(1), 70–86 (2004)Google Scholar
  12. 12.
    Fei, W., Yi, Y., Yueting, Z., Yunhe, P.: Understanding Multimedia Document Semantics for Cross-Media Retrieval. In: Ho, Y.-S., Kim, H.-J. (eds.) PCM 2005. LNCS, vol. 3767, pp. 993–1004. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  13. 13.
    Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B.: Learning with local and global consistency. In: 18th Annual Conf. on Neural Information Processing Systems, pp. 237–244 (2003)Google Scholar
  14. 14.
    Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B.: Ranking on data manifolds. In: 18th Annual Conf. on Neural Information Processing System, pp. 169–176 (2003)Google Scholar
  15. 15.
    Hanghang, T., Jingrui, H., Mingjing, L., Changshui Z., Wei-Ying, M.: Graph based multi-modality learning. In: Proc. ACM Multimedia Conference, Singapore (2005)Google Scholar
  16. 16.
    Shrager, J., Hogg, T., Huberman, B.A.: Observation of phase transitions in spreading activation networks. Science 236, 1092–1094 (1987)CrossRefGoogle Scholar
  17. 17.
    Langville, A.N., Meyer, C.D.: Deeper Inside PageRankGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yueting Zhuang
    • 1
  • Yi Yang
    • 1
  1. 1.College of Computer Science and TechnologyZhejiang University 

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