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Image Annotation with Concept Level Feature Using PLSA+CCA

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Advances in Multimedia Modeling (MMM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6524))

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Abstract

Digital cameras have made it much easier to take photos, but organizing those photos is difficult. As a result, many people have thousands of photos in some miscellaneous folder on their hard disk . If computer can understand and manage these photos for us, we can save time. Also it will be useful for indexing and searching the web images. In this paper we propose an image annotation system with concept level search using PLSA+CCA,which generates the appropriate keywords to annotate the query image using large-scale image database.

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References

  1. Blei, D.M., Jordan, M.I.: Modeling annotated data. In: Proc. ACM SIGIR, pp. 127–134 (2003)

    Google Scholar 

  2. Feng, S.L., Manmatha, R., Lavrenko, V.: Multiple bernoulli relevance models for image and video annotation. In: IEEE Conf. Computer Vision and Pattern Recognition (2004)

    Google Scholar 

  3. Jin, R., Chai, J.Y., Si, L.: Effective automatic image annotation via a coherent language model and active learning. In: ACM Multimedia Conference, pp. 892–889 (2004)

    Google Scholar 

  4. Li, J., Wang, J.: Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (2003)

    Google Scholar 

  5. Barnard, K., Duygulu, P., Forsyth, D., Freitas, N., Blei, D., Jordan, M.: Matching words and pictures. JMLR (2003)

    Google Scholar 

  6. Garneiro, G., Vasconcelos, N.: A Database Centric View of Semantic Image Annotation and Retrieval. In: SIGIR (2005)

    Google Scholar 

  7. Duygulu, P., Barnard, K., de Freitas, J.F.G., Forsyth, D.: Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 97–112. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  8. Barnard, K., Forsyth, D.A.: Learning the semantics of words and pictures. In: ICCV, pp. 408–415 (2001)

    Google Scholar 

  9. Zhang, H., Berg, A., Maire, M., Malik, J.: SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition. In: Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 2126–2136 (June 2006)

    Google Scholar 

  10. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys (2008)

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Zheng, Y., Takiguchi, T., Ariki, Y. (2011). Image Annotation with Concept Level Feature Using PLSA+CCA. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17829-0_43

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  • DOI: https://doi.org/10.1007/978-3-642-17829-0_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17828-3

  • Online ISBN: 978-3-642-17829-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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