인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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
Recently, re-branding has become increasingly popular among overseas famous brands which is the system that replacing creative directors. Among them, Gucci is a successful representative brand. Gucci"s creative director, Alessandro Michele, boasts a genius sense of freedom and harmony that breaks the boundaries of past and present, male and female, eastern and western, with liberal sensibilities. Embroidery is an area of textile art that shows beautiful patterns with various techniques using various materials and tools on the fabric. Gucci, a world-famous brand in the fashion market, positively applied Oriental culture to contemporary fashion. The purpose of this study is to analyze the expression of Chinese traditional embroidery in the Gucci Collection. For this purpose, 122 of the total 698 photographs were analyzed. The photographs for analysis were limited from 2016 S/S to 2018 F/W. Among the expressive elements of Chinese traditional embroidery shown in the Gucci Collection, the patterns were analyzed as animal, plant, geometry, and nature, and the highest score was 51.7% for plants, followed animals, nature, and geometry. As a result of color classification, red, orange, yellow, green, blue, violet, white and black were analyzed. As a result, red color was highest at 26.74%, followed by orange color, yellow color, Green, blue , purple, white, black. It is thought that the highest color of the plants is represented by flowers, leaves and other plants. As embroidery technique and printing technique were analyzed, embroidery was the largest with 75% and printing technique was 15%. I hope that future research will be able to explore more accurate trends of modern fashion for more brands. And I hope this study will help diversify of Chinese traditional embroidery and modern fashion.
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.
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최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2019-300-001251158
