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Related Experiment Videos

Retrieval for color artistry concepts.

Jose A Lay1, Ling Guan

  • 1School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia. jlay@ee.usyd.edu.au

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 21, 2004
PubMed
Summary

This study introduces a new concept-based retrieval engine for artworks, moving beyond the limitations of traditional Query-by-Example systems. It leverages a generative grammar of elemental concepts for semantic searches in color artistry.

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Area of Science:

  • Art History
  • Computer Science
  • Information Retrieval

Background:

  • Current content-based retrieval systems have limited usefulness for complex concepts.
  • The Query-by-Example paradigm is insufficient for nuanced artistic concept retrieval.

Purpose of the Study:

  • To propose a novel concept-based retrieval engine for artworks.
  • To enhance the retrieval of color artistry concepts in visual media.

Main Methods:

  • Developed a generative grammar of elemental concepts for color artistry.
  • Indexed artworks using these elemental concepts.
  • Utilized the generative grammar for post-coordinate expression of concept queries.

Main Results:

  • Demonstrated a concept-based approach for artwork retrieval.

Related Experiment Videos

  • Enabled semantic searches based on color artistry concepts.
  • Overcame limitations of traditional Query-by-Example methods.

    • Conclusions:

    • The proposed concept-based engine offers improved retrieval for color artistry.
    • Generative grammar facilitates sophisticated semantic querying of artworks.
    • This methodology advances content-based image retrieval in art.