Evaluation strategies for image understanding and retrieval

  • Authors:
  • Keiji Yanai;Nikhil V. Shirahatti;Prasad Gabbur;Kobus Barnard

  • Affiliations:
  • University of Electro-Communications, Tokyo, Japan;University of Arizona, Tucson, AZ;University of Arizona, Tucson, AZ;University of Arizona, Tucson, AZ

  • Venue:
  • Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
  • Year:
  • 2005

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Abstract

We address evaluation of image understanding and retrieval large scale image data in the context of three evaluation projects. The first project is a comprehensive strategy for evaluating image retrieval algorithms and provides an open reference data set for doing so. The second project develops word prediction as a semantically relevant evaluation strategy, and applies it to the evaluation of of image processing methods for semantic image analysis. The third project evaluates words for suitability of their visual properties for use in an image annotation framework.