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Annotation-Based Image Retrieval

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Recommended Readings

  1. Long F, Zhang HJ, Feng DD. Fundamentals of content-based image retrieval. In: Feng D, editor. Multimedia information retrieval and management: technological fundamentals and applications. Berlin/Heidelberg: Springer; 2013; Part I. p. 1–26. ISSN: 1860-4862.

    Google Scholar 

  2. Zhang L, Rui Y. Image search from thousands to billions in 20 years. ACM TOMCCAP 2013;9(1s): Article No. 36. Special Issue on the 20th Anniversary of the ACM MM Conference; New York.

    Google Scholar 

  3. Liu Y, Zhang D, Lu G, Ma W-Y. A survey of content-based image retrieval with high-level semantics. Pattern Recogn. 2007;40(1):262–82.

    Article  MATH  Google Scholar 

  4. Rui Y, Huang TS, Chang S-F. Image retrieval: current techniques, promising directions, and open issues. J Vis Commun Image Represent. 1999;10(4):39–62.

    Article  Google Scholar 

  5. Chang S-F, Ma W-Y, Smeulders A. Recent advances and challenges of semantic image/video search. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing; 2007. p. 1205–8.

    Google Scholar 

  6. Blei D, Jordan MI. Modeling annotated data. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2003. p. 127–34.

    Google Scholar 

  7. Jeon J, Lavrenko V, Manmatha R. Automatic image annotation and retrieval using cross-media relevance models. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2003. p. 119–26.

    Google Scholar 

  8. Chang S-F, Chen W, Sundaram H. Semantic visual templates: linking visual features to semantics. In: Proceedings of the International Conference on Image Processing; 1998. p. 531–4.

    Google Scholar 

  9. Zhuang Y, Liu X, Pan Y. Apply semantic template to support content-based image retrieval. In: Proceedings of the SPIE, Storage and Retrieval for Media Databases; 1999. p. 442–9.

    Google Scholar 

  10. Wang X-J, Zhang L, Jing F, Ma W-Y. AnnoSearch: image auto-annotation by search. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition; 2006. p. 1483–90.

    Google Scholar 

  11. Wang X-J, Zhang L, Li X, Ma W-Y. Annotating images by mining image search results. IEEE Trans Pattern Anal Mach Intell. 2008;30(11):1919–32.

    Article  Google Scholar 

  12. Dai LC, Wang X-J, Zhang L, Yu NH. Efficient tag mining via mixture modeling for real-time search-based image annotation. In: Proceedings of the IEEE International Conference on Multimedia and Expo; 2012.

    Google Scholar 

  13. Wang X-J, Zhang L, Ma W-Y. Duplicate-search-based image annotation using web-scale data. Proc IEEE. 2012;100(9):2705–21.

    Article  Google Scholar 

  14. Wang X-J, Zhang L, Liu M, Li Y, Ma W-Y. ARISTA – image search to annotation on billions of web photos. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition; 2010.

    Google Scholar 

  15. Wang X-J, Zhang L, Liu C. Duplicate discovery on 2 billion internet images. IEEE Conference on Computer Vision and Pattern Recognition; 2013.

    Google Scholar 

  16. El-Saban M, Wang X-J, Hasan N, Bassiouny M, Refaat M. Seamless annotation and enrichment of mobile captured video streams in real-time. In: Proceedings of the IEEE International Conference on Multimedia and Expo; 2011.

    Google Scholar 

  17. Zhang X, Zhang L, Wang X-J, Shum H-Y. Finding celebrities in billions of webpages. IEEE Transactions on Multimedia. 2012;14(4):995–1007.

    Article  Google Scholar 

  18. Eakins J, Graham M. Content-based image retrieval. Technical report. Tyne: University of Northumbria at Newcastle; 1999.

    Google Scholar 

  19. Wang X-J, Yu M, Zhang L, Ma W-Y. Advertising based on users’ photos. In: Proceedings of the IEEE International Conference on Multimedia and Expo; 2009.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Microsoft Research Asia, Beijing, China

    Xin-Jing Wang & Lei Zhang

  2. Micros Facebook, CA, USA

    Xin-Jing Wang

  3. Microsoft Research, Redmond, WA, USA

    Lei Zhang

Authors
  1. Xin-Jing Wang
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  2. Lei Zhang
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Corresponding author

Correspondence to Xin-Jing Wang .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. The Chinese University of Hong Kong, Hong Kong, China

    Jeffrey Xu Yu

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Wang, XJ., Zhang, L. (2018). Annotation-Based Image Retrieval. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_17

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