Affiliation:
1. Department of Design, Housing and Apparel, University
of Minnesota, St. Paul, MN 55108.
Abstract
Current apparel production methods grounded in a tradition of master-apprentice training and intuition are being challenged by the introduction of Artificial Intelligence. Much of the expert knowledge needed to develop computer systems for the apparel industry is related to visual decisions made to create a garment. In this study, a sensory evaluation methodology was used to determine if visual perceptual differences existed between results of pattern grading methods using traditional and proportional techniques. An expert panel of eleven members evaluated visual effect of images graded across an entire size range. Three sets of images representing apparel on the body were selected to emphasize (1) horizontal proportion, (2) vertical proportion, and (3) proportion of details. Responses of panel members indicated neither traditional nor proportional grading maintained the visual effect referenced in the sample size across the entire size range. The goal of pattern grading needs to be redefined to account for the desired visual effect in a variety of size and body variations.
Subject
Polymers and Plastics,General Business, Management and Accounting,Materials Science (miscellaneous),Business, Management and Accounting (miscellaneous)
Cited by
7 articles.
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1. An AI-based Clothing Design Process Applied to an Industry-university Fashion Design Class;Journal of the Korean Society of Clothing and Textiles;2023-08-31
2. A Comparative Study of Trouser Pattern Making Methods;Journal of Textile Engineering & Fashion Technology;2017-05-04
3. A Direction for Clothing and Textile Design Research;Clothing and Textiles Research Journal;2010-06-21
4. Optimized pattern grading;International Journal of Clothing Science and Technology;2008-02-29
5. Three-Dimensional Body Scan Data Analysis;Clothing and Textiles Research Journal;2008-02-26