Prosemantic image retrieval

  • Authors:
  • Gianluigi Ciocca;Claudio Cusano;Simone Santini;Raimondo Schettini

  • Affiliations:
  • Università degli Studi di Milano-Bicocca, Milano, Italy;Università degli Studi di Milano-Bicocca, Milano, Italy;Universidad Autónoma de Madrid, Madrid, Spain;Università degli Studi di Milano-Bicocca, Milano, Italy

  • Venue:
  • ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
  • Year:
  • 2012

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Abstract

In this technical demonstration we present a content-based image retrieval system based on the 'query by example' paradigm. The system effectiveness will be proved for both category and target search on two standard image databases, even without a "good" initial example and ancillary information, such as device metadata, text annotations, etc. These results are obtained by incorporating in the system our recently proposed prosemantic features coupled with a relevance feedback mechanism, and by maximizing novelty and diversity in the result sets.