Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Database Systems pp 228–236Cite as

Automatic Image Annotation

  • Reference work entry
  • First Online:

  • 183 Accesses

Synonyms

Auto-annotation; Image classification; Multimedia content enrichment; Object detection and recognition

Definition

The widespread search engines, in the professional as well as the personal context, used to work on the basis of textual information associated or extracted from indexed documents. Nowadays, most of the exchanged or stored documents have multimedia content. To reduce the technological gap so that these engines still can work on multimedia content, it is very convenient developing methods capable to generate automatically textual annotations and metadata. These methods will then allow to enrich the upcoming new content or to post-annotate the existing content with additional information extracted automatically if ever this existing content is partly or not annotated.

A broad diversity in the typology of manual annotation is usually found in image databases. Part of them is representing contextual information. The author, date, place or technical shooting conditions...

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Recommended Reading

  1. Smeulders AWM, Worring M, Santini S, Gupta A, Jain R. Content-based image retrieval at the end of the early years. IEEE Trans Pattern Analy Machine Intell. 2000;22(12):1349–80.

    Article  Google Scholar 

  2. Boujemaa N., Fauqueur J., and Gouet V. What’s beyond query by example? Technical report, INRIA; 2003.

    Google Scholar 

  3. Hare JS, Lewis PH, Enser PGB, Sandom CJ. Mind the gap: another look at the problem of the semantic gap in image retrieval. In: Proceedings of the SPIE: Multimedia Content Analysis, Management, and Retrieval; 2006.

    Google Scholar 

  4. Boujemaa N, Fauqueur J, Ferecatu M, Fleuret F, Gouet V, Le Saux B, Sahbi H. Ikona: interactive specific and generic image retrieval. In: Proceedings of the International Workshop on Multimedia Content-Based Indexing and Retrieval; 2001. Available at: http://www-rocg.inria.fr/imedia/mmcbirzod.html.

  5. Szummer M, Picard RW. Indoor-outdoor image classification. In: Proceedings of the Workshop on Content-Based Access to Image and Video Databases; 1998.

    Google Scholar 

  6. Vailaya A, Jain A, Zhang H-J. On image classification: city images vs. landscapes. Pattern Recogn J. 1998;31(12):1921–35.

    Article  Google Scholar 

  7. Enser PGB, Sandom CJ, Lewis PH. Automatic annotation of images from the practitioner perspective. In: Proceedings of the 4th International Conference. Image and Video Retrieval; 2005. p. 497–506.

    Google Scholar 

  8. Datta R, Li J, Wang JZ. Content-based image retrieval – approaches and trends of the new age. In: Proceedings of the 7th ACM SIGMM International Workshop on Multimedia Information Retrieval; 2005. p. 253–62.

    Google Scholar 

  9. Hanjalic A, Sebe N, Chang E. Multimedia content analysis, management and retrieval: trends and challenges. In: Proceedings of the SPIE: Multimedia Content Analysis, Management, and Retrieval; 2006.

    Google Scholar 

  10. Lew MS, Sebe N, Djeraba C, Jain R. Content-based multimedia information retrieval: state of the art and challenges. ACM Trans Multimedia Comp Comm Appl. 2006;2(1):1–19.

    Article  Google Scholar 

  11. Ponce J, Hebert M, Schmid C, Zisserman A, editors. Toward category-level object recognition, Lecture notes in computer science. New York: Springer;2006.

    Google Scholar 

  12. Hervé N, Boujemaa N. Image annotation: which approach for realistic databases? In: Proceedings of the 6th ACM International Conference Image and Video Retrieval; 2007. p. 170–7.

    Google Scholar 

  13. Barnard K, Duygulu P, Forsyth D, de Freitas N, Blei DM, Jordan MI. Matching words and pictures. J Mach Learn Res. 2003;3(6):1107–35.

    MATH  Google Scholar 

  14. Opelt A, Pinz A, Fussenegger M, Auer P. Generic object recognition with boosting. Pattern Anal Mach Intell. 2006;28(3):416–31.

    Article  MATH  Google Scholar 

  15. Zhang J, Marszalek M, Lazebnik S, Schmid C. Local features and kernels for classification of texture and object categories: a comprehensive study. Int J Comput Vis. 2007;73(2):213–38.

    Article  Google Scholar 

  16. Amores J, Sebe N, Radeva P. Context-based object-class recognition and retrieval by generalized correlograms. IEEE Trans Pattern Anal Mach Intell. 2007;29(10):1818–33.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. INRIA Paris-Rocquencourt, Le Chesnay, France

    Nicolas Hervé & Nozha Boujemaa

Authors
  1. Nicolas Hervé
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nozha Boujemaa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nicolas Hervé .

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. Dept. of Computer Science, New Jersey Inst. of Technology, Newark, NJ, USA

    Vincent Oria

  2. Digital Content and Media Sciences ReseaMultimedia Information Research Division, National Institute of Informatics, Tokyo, Japan

    Shin'ichi Satoh

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Hervé, N., Boujemaa, N. (2018). Automatic Image Annotation. 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_1010

Download citation

Publish with us

Policies and ethics

Search

Navigation