• DocumentCode
    2834618
  • Title

    Sensitivity Characterization by Impression and Color Words

  • Author

    Ishii, Naohiro ; Tokuda, Yusaku ; Torii, Ippei ; Kanda, Tomomi

  • Author_Institution
    Dept. of Inf. Sci., Aichi Inst. of Technol., Toyota, Japan
  • fYear
    2009
  • fDate
    2-4 Nov. 2009
  • Firstpage
    362
  • Lastpage
    369
  • Abstract
    Paintings have some sensibility information to human hearts. But, the sensibility information will be different to person to person. We like some paintings, while other persons like another ones. For appreciation of paintings, grouping of paintings with similar sensitivity will be helpful. In this paper, we developed a distance measure relation among paintings for similarity grouping. Four similarity relations (types) are developed by the distance measure for classification of paintings. Impression words and color words play an important role for the sensibility expression of paintings. To verify the combination of these words, a self-organizing map (SOM) by two layered neural network, was applied for the grouping of paintings. It was shown that the combination of the impression words and color ones make a well similar grouping of paintings. Grouping similar paintings in impression words and color ones will be useful for a recommendation system.
  • Keywords
    image classification; image colour analysis; self-organising feature maps; color words; impression words; painting classification; recommendation system; self-organizing map; sensitivity characterization; two layered neural network; Art; Artificial intelligence; Earth; Heart; Humans; Image databases; Information science; Multimedia databases; Neural networks; Painting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on
  • Conference_Location
    Newark, NJ
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4244-5619-2
  • Electronic_ISBN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2009.50
  • Filename
    5364347