Automatic Image Tagging Using Community-Driven Online Image Databases

  • Marius Renn
  • Joost van Beusekom
  • Daniel Keysers
  • Thomas M. Breuel
Conference paper

DOI: 10.1007/978-3-642-14758-6_10

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5811)
Cite this paper as:
Renn M., van Beusekom J., Keysers D., Breuel T.M. (2010) Automatic Image Tagging Using Community-Driven Online Image Databases. In: Detyniecki M., Leiner U., Nürnberger A. (eds) Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music. AMR 2008. Lecture Notes in Computer Science, vol 5811. Springer, Berlin, Heidelberg

Abstract

Automatic image tagging is becoming increasingly important to organize large amounts of image data. To identify concepts in images, these tagging systems rely on large sets of annotated image training sets. In this work we analyze image sets taken from online community-driven image databases, such as Flickr, for use in concept identification. Real-world performance is measured using our flexible tagging system, Tagr.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marius Renn
    • 1
  • Joost van Beusekom
    • 1
  • Daniel Keysers
    • 1
  • Thomas M. Breuel
    • 1
  1. 1.IUPR GroupTechnical University of KaiserslauternGermany

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