• DocumentCode
    677868
  • Title

    Affective Engineering for Streetscape Analysis: Evaluation of Traditional Japanese Mud Walls Using a Self-Organizing Map

  • Author

    Nagaoka, A. ; Ogawa, Rina ; Tsuchiya, Takao

  • Author_Institution
    Fac. of Econ., Shimonoseki City Univ., Shimonoseki, Japan
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    1132
  • Lastpage
    1137
  • Abstract
    Affective/Kansei engineering is used to analyze subjective responses to a streetscape plan for a historic townscape. The Chofu area in Shimonoseki was chosen for the research. The appearance of the streetscape is evaluated based on actual photographs using a traditional semantic differential method. Guidelines are often formulated to promote landscaping plans in historic towns, it is especially important to formulate color guidelines so as to unify the colors in an area undergoing change. The affective engineering proposed in this study reveals representative design elements arising from the regional characteristics of the area and its people. The pilot investigation using a self-organizing map validated the evaluation of mud wall colors.
  • Keywords
    history; image colour analysis; self-organising feature maps; town and country planning; walls; Chofu area; Kansei engineering; Shimonoseki; affective engineering; area regional characteristics; color guidelines; historic townscape; landscaping plans; mud wall color evaluation; people regional characteristics; photographs; representative design elements; self-organizing map; streetscape analysis; traditional Japanese mud walls; traditional semantic differential method; Correlation; Guidelines; Histograms; Image color analysis; Semantics; Surface texture; Vectors; SOM; affective engineering; mud wall;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.197
  • Filename
    6721950