@Article{JFBI-6-453,
author = {},
title = {Lower Body Classification of Young Women for Pants Size Optimization},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2013},
volume = {6},
number = {4},
pages = {453--465},
abstract = {Pants fit have always been a problem in China's pant market. To qualitatively improve how well pants
fit consumers, we analyzed the lower body shapes of 179 young women from an anthropometric aspect.
We first used a 3D measuring method to obtain 85 measurements related to lower body shape. Then, by
applying principal component factor analysis method, we used 7 principal components to describe lower
body shape. The first 2 factors, heavy-thin factor and abdomen-hip factor, had the highest cumulative
contribution rate, 40.475%. Therefore, the hipline of the first principal component and the abdomen-hip
differential of the second principal component were used as 2 key indexes to classify the lower body into
9 types. After using both the interior extrapolation method based on interval division and the k-means
cluster method to further classify the lower body shape, we concluded that the former is more suitable.
Therefore, we classified lower body shape into 9 types, the coverage of which reached 80.45% of the total
samples. By taking both the degree of stoutness of the lower body and the difference of abdomen-hip
shape into consideration, this classification can provide a theoretical basis for pants size optimization to
improve pants fit in the waist, abdomen, and hip portions.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbi12201309},
url = {http://global-sci.org/intro/article_detail/jfbi/4855.html}
}