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Finding Visual Concepts by Web Image Mining

  • Keiji Yanai, University of Electro-Communications, Japan
  • Kobus Barnard, University of Arizona, USA

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Track: Posters

We propose measuring ``visualness'' of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is yet another application of ``Web image mining''. To know which concept has visually discriminative power is important for image recognition, especially automatic image annotation by image recognition system, since not all concepts are related to visual contents. Our method performs probabilistic region selection for images which are labeled as concept ``X'' or ``non-X'', and computes an entropy measure which represents ``visualness'' of concepts. In the experiments, we collected about forty thousand images from the World-Wide Web using the Google Image Search for 150 concepts. We examined which concepts are suitable for annotation of image contents.


Yanai, K. and Barnard, K. 2006. Finding visual concepts by web image mining. In Proceedings of the 15th International Conference on World Wide Web (Edinburgh, Scotland, May 23 - 26, 2006). WWW '06. ACM Press, New York, NY, 923-924.
DOI= http://doi.acm.org/10.1145/1135777.1135946

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