Finding visual concepts by web image mining

Keiji Yanai, Kobus Barnard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web image mining". To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.

Original languageEnglish (US)
Title of host publicationProceedings of the 15th International Conference on World Wide Web
Pages923-924
Number of pages2
DOIs
StatePublished - Dec 1 2006
Event15th International Conference on World Wide Web - Edinburgh, Scotland, United Kingdom
Duration: May 23 2006May 26 2006

Publication series

NameProceedings of the 15th International Conference on World Wide Web

Other

Other15th International Conference on World Wide Web
CountryUnited Kingdom
CityEdinburgh, Scotland
Period5/23/065/26/06

Keywords

  • Image recognition
  • Probabilistic method
  • Web image mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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  • Cite this

    Yanai, K., & Barnard, K. (2006). Finding visual concepts by web image mining. In Proceedings of the 15th International Conference on World Wide Web (pp. 923-924). (Proceedings of the 15th International Conference on World Wide Web). https://doi.org/10.1145/1135777.1135946