Abstract
AbstractThe aim of this study is to develop algorithms for automatic landmark extraction on women with various upper body types and body inclinations using the Grasshopper algorithm editor, which enables the user to interact with the 3D modeling interface. First, 15 landmarks were defined based on the morphological features of 3D body surfaces and clothing applications, from which automatic landmark extraction algorithms were developed. To verify the accuracy of the algorithms on various body shapes, this study determined criteria for key body shape factors (BMI, neck slope, upper body slope, and shoulder slope) that influence each landmark position, classified them into body shape groups and sorted the scan samples for each body type using the 6th SizeKorea database. The statistical differences between the scan-derived measurements and the SizeKorea measurements were compared, with an allowable tolerance of ISO 20685. In the case of landmarks with significant differences, the algorithm was modified. It was found that the algorithms were successfully applied to various upper body shapes, which improved the reliability and accuracy of the algorithm.
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Subject
Marketing,Strategy and Management,Materials Science (miscellaneous),Cultural Studies,Social Psychology
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