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Linking KANSAI and Image Features by Multi-layer Neural Networks

  • Xinyin Huang
  • Shouta Sobue
  • Tomoki Kanda
  • Yen-Wei Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4693)

Abstract

KANSEI is a Japanese term which means psychological feeling or image of a product. KANSEI engineering refers to the translation of consumers’ psychological feeling about a product into perceptual design elements. Recently several researches have been done for image indexing or image retrieval based on KANSEI factors. In this paper, we report a quantitative study on relationship between image color features and human KNASEI factors. We use the semantic differential (SD) method to extract the KANSEI factors (impressions) such as bright, warm from 4 group subjects (Children, students, adults, elderly person) while they viewing an image (painting). A neural network is used to learn the mapping functions (relationships) from the image feature space to human KANSEI factor space (psychological space).

Keywords

KANSEI impression image color neural network SD method 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Xinyin Huang
    • 1
  • Shouta Sobue
    • 2
  • Tomoki Kanda
    • 2
  • Yen-Wei Chen
    • 2
  1. 1.School of Education, Soochow University, Suzhou, Jiangsu 215006China
  2. 2.College of Information Science and Eng., Ritsumeikan Univ., Shiga, 525-8577Japan

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