A quantitative classification of body shape by 3-D measurement data

本研究旨在展示年轻女性的肩型，建立肩型类型分类方法，并通过三维测量数据对肩型进行分类，因为肩部支撑服装，该部位的合身程度影响着服装的舒适度。首先，为了确定用于本研究的非接触式三维数字化仪的最佳摄影条件和精度，进行了三次实验。结果明确了最佳的摄像机水平和角度，证实了三维数据的精度较好，但也指出了对人体摇摆的注意。接下来，在2004年11月至12月期间，63名女学生志愿者被三维数字化仪拍摄。对三维图像和三维坐标值计算的19个项目进行分析，考察平均肩型和个体差异。然后对这11个项目进行主成分分析，提取表达肩形的因子，并利用聚类分析的成分得分对肩形进行分类。主要研究结果如下：从三维图像上看，他们的肩部形状各异，肩部和颈部的大小存在较大的个体差异。肩前曲率与肩斜、颈底深度与颈宽之间的相关性很低，因此它们是相互独立的。作为主成分分析的结果，我们提取了三个主成分；第一个分量表示肩部的大小和肩部向前弯曲的程度，第二个分量表示肩部的坡度、颈底的坡度和前胸的圆度，第三个分量表示前胸的宽度和颈底的宽度。然后利用成分得分聚类分析，将其肩型分为4类。只有两个人属于第四组，所以我们试图解释其他三个组。第一组为平均肩型，第二组为方肩型，颈底坡度小，胸围丰满，第三组肩宽、肩深较小，背宽相对较窄。少

This study aimed to show the young women's shoulder shape, to establish the method of shoulder shape type classification, and to classify the shoulder shape by 3-D measurement data, because the shoulder part supports clothing and the fitting to this part influences the comfortableness of clothing.First, in order to confirm the optimum photography conditions and the precision of a non-contact 3-D digitizer used for this study, three experiments were conducted. As the results, the optimum level and angle of camera were clarified, and it was confirmed that the precision of 3-D data was good, however, it was indicated that the cautions to the sway of human body are required. Next, sixty-three female student volunteers were photographed by 3-D digitizer from November to December in 2004. The three-dimensional pictures and the 19 items computed from the 3-D coordinate values were analyzed to examine the average shoulder shape and the individual differences. Then we applied the principal comp … More onent analysis to the 11 items to extract factors which express the shoulder shapes, and tried to classify the shoulder shapes, using the component scores by cluster analysis.The main results are as follow ; their shoulder shapes by 3-D pictures are various and the sizes on shoulder and neck parts have large individual differences. The correlations between shoulder curvature forward and shoulder slope and between neck base depth and width are very low, therefore, they are independent. As the results of principal component analysis, we extracted three principal components ; the first component which express the shoulder size and the degree of shoulder curvature forward, the second component which express the shoulder slope, the neck-base slope, and the roundness of front chest, and the third component which express the front chest width and the neck-base width. Then using cluster analysis of component score, we classified their shoulder shapes to 4 groups. Only two members belong to the fourth group, so we tried to interpreter about the rest three groups. The first group has the average shoulder type, the second group has the square shoulder, the small neck-base slope, and the full bust, and the third group has the small shoulder width and depth and the narrow back width relatively. Less