Skip to main content

Automatic Image Annotation

  • Reference work entry
Encyclopedia of Database Systems
  • 377 Accesses

Synonyms

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

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 to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 2,500.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Amores J., Sebe N., and Radeva P. Context-based object-class recognition and retrieval by generalized correlograms. IEEE Trans. Pattern Anal. Mach. Intell., 29(10):1818–1833, 2007.

    Article  Google Scholar 

  2. Barnard K., Duygulu P., Forsyth D., de Freitas N., Blei D.M., and Jordan M.I. Matching words and pictures. J. Mach. Learn. Res., 3:1107–1135, 2003.

    Google Scholar 

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

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

    Google Scholar 

  5. Datta R., Li J., and Wang J.Z. Content-based image retrieval – approaches and trends of the new age. In Proc. 7th ACM SIGMM Int. Workshop on Multimedia Information Retrieval, 2005, pp. 253–262.

    Google Scholar 

  6. Enser P.G.B., Sandom C.J., and Lewis P.H. Automatic annotation of images from the practitioner perspective. In Proc. 4th Int. Conf. Image and Video Retrieval, 2005, pp. 497–506.

    Google Scholar 

  7. Hanjalic A., Sebe N., and Chang E. Multimedia content analysis, management and retrieval: trends and challenges. In Proc. SPIE: Multimedia Content Analysis, Management, and Retrieval, 2006.

    Google Scholar 

  8. Hare J.S., Lewis P.H., Enser P.G.B., and Sandom C.J. Mind the gap: another look at the problem of the semantic gap in image retrieval. In Proc. SPIE: Multimedia Content Analysis, Management, and Retrieval, 2006.

    Google Scholar 

  9. Hervé N. and Boujemaa N. Image annotation: which approach for realistic databases? In Proc. 6th ACM Int. Conf. Image and Video Retrieval, 2007, pp. 170–177.

    Google Scholar 

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

    Google Scholar 

  11. Opelt A., Pinz A., Fussenegger M., and Auer P. Generic object recognition with boosting. Pattern Anal. Mach. Intell., 28(3):416–431, 2006.

    Article  Google Scholar 

  12. Ponce J., Hebert M., Schmid C., and Zisserman A (eds.). Toward category-level object recognition. Springer-Verlag Lecture Notes in Computer Science, 2006.

    Google Scholar 

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

    Article  Google Scholar 

  14. Szummer M. and Picard R.W. Indoor-outdoor image classification. In Proc. Workshop on Content-based Access to Image and Video Databases, Bombay, 1998.

    Google Scholar 

  15. Vailaya A., Jain A., and Zhang H-J. On image classification: city images vs. landscapes. Pattern Recognit. J., 31(12):1921–1935, 1998.

    Article  Google Scholar 

  16. Zhang J., Marszalek M., Lazebnik S., and Schmid C. Local features and kernels for classification of texture and object categories: a comprehensive study. Int. J. Comput. Vis., 73(2):213–238, 2007.

    Article  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 Science+Business Media, LLC

About this entry

Cite this entry

Hervé, N., Boujemaa, N. (2009). Automatic Image Annotation. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1010

Download citation

Publish with us

Policies and ethics