지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.10
- 수록면
- 423 - 435 (13page)
- DOI
- 10.5143/JESK.2020.39.5.423
이용수
초록· 키워드
오류제보하기
Objective: By establishing the weight relationship between the factors of interior colour and perceptual semantics and using it as a guide, designers can more quickly and more accurately design the interior colours thatusers desire.
Background: From past work experience, it was found that, due to differences in cognition and understanding in the process of communicating with users, the final design effects often cannot accurately reflect the real needs of our users. This challenge results in repeated communication and modification, which costs a considerable amount of time and greatly reduces the work efficiency. Kansei Engineering can solve this problem effectively. The existing research of Kansei Engineering is mainly focused on the terms of automobiles and products, with just a few related to interior design.
Method: By analysing the principle of interior colour collocation, typical original samples were selected with focus groups to create research samples of immersive 3D panoramic renderings for experiments. Through a questionnaire survey, user"s perceptual images of the ideal home space and typical samples were collected. The most suitable perceptual semantic vocabulary for the samples were then selected by means of factor analysis. Taking the word "concise" as an example, we first employed the fuzzy matrix analysis method to calculate the weight value of each color design factor at each level (expert group), and then used the Likert scale to investigate user data (user group). Finally, the above two groups of data were combined to form the final weight value of each interior color design factor for the perceptual semantic word "concis".
Results: The model can effectively analyse the weight values between the perceptual semantic word "concise" and various interior colour design factors. Among the secondary factors, the furniture hue is the highest in the comprehensive weight value, and among the third factors, the furniture colour white is the highest of all factors.
Conclusion: The model that combines Kansei Engineering, factor analysis and fuzzy hierarchical analysis can effectively calculate the weight value of the perceptual semantic vocabulary in each design factor. It has direct significance for designers and provides new ideas for further realization of AI-automated interior design.
Application: The research on home interior colour design based on immersive VR rendering experience can be applied to the design scheme phase of home interior design projects.
Background: From past work experience, it was found that, due to differences in cognition and understanding in the process of communicating with users, the final design effects often cannot accurately reflect the real needs of our users. This challenge results in repeated communication and modification, which costs a considerable amount of time and greatly reduces the work efficiency. Kansei Engineering can solve this problem effectively. The existing research of Kansei Engineering is mainly focused on the terms of automobiles and products, with just a few related to interior design.
Method: By analysing the principle of interior colour collocation, typical original samples were selected with focus groups to create research samples of immersive 3D panoramic renderings for experiments. Through a questionnaire survey, user"s perceptual images of the ideal home space and typical samples were collected. The most suitable perceptual semantic vocabulary for the samples were then selected by means of factor analysis. Taking the word "concise" as an example, we first employed the fuzzy matrix analysis method to calculate the weight value of each color design factor at each level (expert group), and then used the Likert scale to investigate user data (user group). Finally, the above two groups of data were combined to form the final weight value of each interior color design factor for the perceptual semantic word "concis".
Results: The model can effectively analyse the weight values between the perceptual semantic word "concise" and various interior colour design factors. Among the secondary factors, the furniture hue is the highest in the comprehensive weight value, and among the third factors, the furniture colour white is the highest of all factors.
Conclusion: The model that combines Kansei Engineering, factor analysis and fuzzy hierarchical analysis can effectively calculate the weight value of the perceptual semantic vocabulary in each design factor. It has direct significance for designers and provides new ideas for further realization of AI-automated interior design.
Application: The research on home interior colour design based on immersive VR rendering experience can be applied to the design scheme phase of home interior design projects.
목차
1. Introduction
2. Method
3. Results
4. Discussion
References
참고문헌 (13)
참고문헌 신청
Yu-Ming Chang / 2016 / Kansei assessment of the constituent elements and the overall interrelations in car steering wheel design / International Journal of Industrial Ergonomics 56:97~105
Hanada, M. / 2017 / Correspondence analysis of color-emotion associations / Color Research & Application 43(2):224~237
Weixin Huang / 2018 / Interior Color Preference Investigation Using Interactive Genetic Algorithm / Journal of Asian Architecture and Building Engineering 8(2):439~445
Liu, X. Y. / 2018 / Application of Metaphorical Characteristics of Color in Mobile Phone UI Design / Packaging Engineering 39(8):200~204
Luo, L. X. / 2015 / Perceptual engineering design
Hanada, M. / 2017 / Correspondence analysis of color-emotion associations / Color Research & Application 43(2):224~237
Weixin Huang / 2018 / Interior Color Preference Investigation Using Interactive Genetic Algorithm / Journal of Asian Architecture and Building Engineering 8(2):439~445
Liu, X. Y. / 2018 / Application of Metaphorical Characteristics of Color in Mobile Phone UI Design / Packaging Engineering 39(8):200~204
Luo, L. X. / 2015 / Perceptual engineering design
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