Abstract
AbstractFashion image datasets, in which each fashion image has a label indicating its design attributes and styles, have contributed to the achievement of various machine learning techniques in the fashion industry. Computer vision studies have investigated labeling categories (such as fashion items, colors, materials, details, and styles) to create fashion image datasets for supervised learning. Although a considerable number of fashion image datasets has been developed, different style classification criteria exist because of a lack of understanding concerning fashion style. Since fashion styles reflect various design attributes, multiple styles can often be included in a single outfit. Thus, this study aims to build a Hybrid Style Framework to develop a fashion image dataset that can be efficiently applied to supervised learning. We conducted focus group interviews with six fashion experts to determine fashion style categories with which to classify hybrid styles in fashion images. We developed 1,206,931K-fashion image datasets and analyzed the hybrid style convergence. Finally, we applied the datasets to the machine learning model and verified the accuracy of the computer’s ability to recognize style. Overall, this study concludes that the Hybrid Style Framework and developed K-fashion image datasets are helpful, as they can be applied to data-driven fashion services to offer personalized fashion design solutions.
Funder
National Information Society Agency
Publisher
Springer Science and Business Media LLC
Subject
Marketing,Strategy and Management,Materials Science (miscellaneous),Cultural Studies,Social Psychology
Reference44 articles.
1. Ahn, B., & Geum, K. S. (2016). A study on the situation and perspective of K-fashion. Journal of Basic Design & Art, 17(1), 349–362.
2. An, H., Kim, S., & Choi, Y. (2021). Sportive fashion trend reports: A hybrid style analysis based on deep learning techniques. Sustainability, 13(17), 9530. https://doi.org/10.3390/su13179530
3. An, H., Kwon, S., & Park, M. (2019). A case study on the recommendation services for customized fashion styles based on artificial intelligence. Journal of the Korean Society of Clothing and Textiles, 43(3), 349–360. https://doi.org/10.5850/JKSCT.2019.43.3.349
4. Choe, S. (2021). From BYS to ‘Squid Game’: How South Korea became a cultural juggernaut. The New York Times. https://www.nytimes.com/2021/11/03/world/asia/squid-game-korea-bts.html. Accessed 4 May 2022.
5. Chung, I., & Rhee, E. (1993). A study on the hierarchy of clothing images. Journal of the Korean Society of Clothing and Textiles, 17(4), 529–538.
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献