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Multimedia Tools and Applications

, Volume 51, Issue 1, pp 303–339 | Cite as

Context modeling in computer vision: techniques, implications, and applications

  • Oge MarquesEmail author
  • Elan Barenholtz
  • Vincent Charvillat
Article

Abstract

In recent years there has been a surge of interest in context modeling for numerous applications in computer vision. The basic motivation behind these diverse efforts is generally the same—attempting to enhance current image analysis technologies by incorporating information from outside the target object, including scene analysis as well as metadata. However, many different approaches and applications have been proposed, leading to a somewhat inchoate literature that can be difficult to navigate. The current paper provides a ‘roadmap’ of this new research, including a discussion of the basic motivation behind context-modeling, an overview of the most representative techniques, and a discussion of specific applications in which contextual modeling has been incorporated. This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context modeling in their own work.

Keywords

Computer vision Object recognition Objects in context Context modeling 

Notes

Acknowledgements

The authors would like to thank Geraldine Morin, Pierre Gurdjos, Viorica Patraucean, and Jerôme Guenard, for the insightful discussions and constructive suggestions.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Oge Marques
    • 1
    Email author
  • Elan Barenholtz
    • 1
  • Vincent Charvillat
    • 2
  1. 1.Florida Atlantic UniversityBoca RatonUSA
  2. 2.ENSEEIHTToulouseFrance

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