基于小波系数的青年女性体型分类及原型纸样

Young female body shape classification and prototype patterns based on wavelet coefficient

为建立基于纵截面曲线形态指标细分青年女性躯干体型的方法,选择了257名在校青年女性,使用扫描仪获得三维人体数据,借助Imageware逆向工程软件,对人体点云数据进行精简处理,通过三次样条函数对提取的纵截面轮廓点云数据进行拟合,运用小波去噪进行处理;利用小波分析的低频系数作为提取信号的总体特征,用Davies-Bouldin指标确定最佳聚类数目,利用K-means聚类算法进行体型聚类,获得4类不同的体型,描述了各类体型在前后中心线、背部、胸部、臀部、肩部和侧缝的体型特征差异;最后构建4类体型对应的原型纸样,并分析纸样与人体体型间的关系,可为青年女性原型纸样的合体性设计提供参考。

In order to establish a method of subdividing young female＇ s torso shapes based on the morphology of the longitudinal section curve,257 young college female students were selected.3-D human body was acquired by a scanner.Point cloud data of human body was simplified using reverse engineering software of Imageware.Point cloud data of longitudinal section profile curve was fitted by the cubic spline function,and subjected to wavelet denoising.Low frequency coefficient for wavelet analysis was used to extract overall characteristic of signals.As for shape clustering the K-means cluster analysis was used,and the Davies-Bouldin was used to determine the optimal class number.Human body shapes could be classified into four types.The difference on all kinds of shapes on front/back center line,back,chest and hip were described.Finally,the prototype patterns of four types of body shapes were built,and the relationships between patterns and body shapes were analyzed,which provides the reference basis for the fitness design of young female＇s patterns.