인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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.
피인용 0
초록·키워드
Background : Emotions are complex conscious states that play an essential role in our daily lives. They have a great influence on human perception, particularly concerning our thinking, learning and decisions. In design, product emotion plays an important role in encouraging product quality and sustainability. Several methods and tools exist and are used to in the process of evaluating users-emotional experiences with products. Emotion is important to design because virtually all the decisions we make are based on how we feel or how we anticipate we will feel. Kansei engineering is a consumer-oriented technique for new product development. In product design, for instance, clothing and fabric design can be applied to translate consumers’ favorite feelings or images into physical design elements.
Methods : This paper aims to develop the process of evaluating users’ emotional experiences in a more accurate semantic dimension through Kansei. Image feature extraction is a key issue for concept recognition in images and particularly emotions. In analyzing the product images, KJ methods based on the affective model was used to develop the full range of emotional keywords. This method shows the potentiality, limitation and building of a new framework for understanding the semantic structure used by designers in the visual analysis process for fabric analysis of clothing. Another affective model from SD methods also needed to support all the data.
Result : The results show that various methods of the affective model will be a good reference for design studies that are involved with users’ subjective emotional experience with product design. The emotional expression showed that it can be well engaged in the process of satisfied and dissatisfied or desired or undesired in product choices.
Conclusions : The process of identifying consumer needs is an integral part of the larger product development process and most closely related to the conceptual design, design selection, competitive benchmarking and establishment of product specification. Kansei methods will lead to better perceptions and understanding of product images and forms.
Methods : This paper aims to develop the process of evaluating users’ emotional experiences in a more accurate semantic dimension through Kansei. Image feature extraction is a key issue for concept recognition in images and particularly emotions. In analyzing the product images, KJ methods based on the affective model was used to develop the full range of emotional keywords. This method shows the potentiality, limitation and building of a new framework for understanding the semantic structure used by designers in the visual analysis process for fabric analysis of clothing. Another affective model from SD methods also needed to support all the data.
Result : The results show that various methods of the affective model will be a good reference for design studies that are involved with users’ subjective emotional experience with product design. The emotional expression showed that it can be well engaged in the process of satisfied and dissatisfied or desired or undesired in product choices.
Conclusions : The process of identifying consumer needs is an integral part of the larger product development process and most closely related to the conceptual design, design selection, competitive benchmarking and establishment of product specification. Kansei methods will lead to better perceptions and understanding of product images and forms.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-ECN-0101-2016-658-002393412
