Shape Generation Based on Personal Points of Attention-Externalization of Latent Kansei by Noting User's Points of Attention
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- YANAGISAWA Hideyoshi
- School of Engineering, The University of Tokyo
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- MURAKAMI Tamotsu
- School of Engineering, The University of Tokyo
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- FUKUDA Shuichi
- School of Intelligent Systems, Tokyo Metropolitan University
Bibliographic Information
- Other Title
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- 個人の注目特徴に基づく形状創成(注目特徴の明示化による潜在的感性の外在化)
- コジン ノ チュウモク トクチョウ ニ モトヅク ケイジョウ ソウセイ チュウモク トクチョウ ノ メイジカ ニ ヨル センザイテキ カンセイ ノ ガイザイカ
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Abstract
In this paper, the authors propose a shape generation method based on the personal Kansei. The method works through an interaction between the user and a computer system. Several methods have been proposed to externalize “Tacit Kansei”, which is difficult to externalize the objective information such as words, although the user notices in his/her mind, up to now. On the other hand, “Latent Kansei”, which the user does even not notice in his mind, has not been discussed. The authors focus on Latent Kansei. The purpose of the method is to help the user to evoke the Latent Kansei by noting user's points of attention. A computer system generates new design samples based on the points of attention selected by the user. Reduct calculation in rough set theory is applied to estimate the features. The user externalizes both of Latent and Tacit Kansei through the iteration of the interaction process: generating design samples, showing the user's point of attention and evaluating design samples by the user. The system was compared to a conventional design system in which the user adjusts the design parameters by him/herself, and effectiveness of the system is demonstrated by experiments of shape design.
Journal
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- Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
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Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 18 (4), 534-544, 2006
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390282680164373760
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- NII Article ID
- 110004814939
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- NII Book ID
- AA1181479X
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- ISSN
- 18817203
- 13477986
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- NDL BIB ID
- 8069718
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed