体型
特征(语言学)
参数统计
参数化模型
人工智能
体表
参数曲面
人体
计算机科学
几何形状
模式识别(心理学)
工程类
数学
几何学
统计
哲学
语言学
作者
Jun Wang,Xiaojiu Li,Li Pan,Chunyuan Zhang
标识
DOI:10.1016/j.ergon.2021.103142
摘要
Abstract Three-dimensional (3D) human body modeling is an important research direction in the field of clothing virtual design. On the basis of 3D human body scanning, this paper studied a method to build a 3D parametric lower body model according to body classification. The research includes three main parts. (1) Anthropometry and body shape classification. We randomly selected 333 young women ages 18–25 years old in Northeast China as the experimental sample. Then we divided the lower body shape into three categories using principal component analysis and K-means clustering. (2) Determination of feature cross sections and points, and reconstruction of feature curves. According to the average values of each body type, we obtained the mean reference body by Euclidean distance method. We determined feature cross sections and points, and extracted the 3D coordinates of the feature points of the mean reference body to reconstruct the feature curves. (3) The surface lofting and establishment of parametric 3D lower body model. According to the shape characteristics of the lower body, we constructed the guiding lines for the crotch and lower limbs, and established parametric lower body models for three body types. Relevance to industry 3D human modeling is an important part of garment industry digitization. This research provides an effective way to construct a parametric 3D lower body model. The method offers a reference for the parametric virtual human modeling and virtual fitting of trousers.
科研通智能强力驱动
Strongly Powered by AbleSci AI