Lower Body Classification of Young Women for Pants Size Optimization (Journal of Fiber Bioengineering and Informatics, 2013)
Pants fit have always been a problem in China's pant market. To qualitatively improve how well pantsfit 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, byapplying principal component factor analysis method, we used 7 principal components to describe lowerbody shape. The first 2 factors, heavy-thin factor and abdomen-hip factor, had the highest cumulativecontribution rate, 40.475%. Therefore, the hipline of the first principal component and the abdomen-hipdifferential of the second principal component were used as 2 key indexes to classify the lower body into9 types. After using both the interior extrapolation method based on interval division and the k-meanscluster 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 totalsamples. By taking both the degree of stoutness of the lower body and the difference of abdomen-hipshape into consideration, this classification can provide a theoretical basis for pants size optimization toimprove pants fit in the waist, abdomen, and hip portions.