摘要
体型分类参数是服装智能化生产的关键要素,是制衣技术精细化的重要前提,而体型模型的建立与预测是当前服装行业的重要研究课题。为分析目前老年男性亟待解决的裤装适体性问题,通过三维人体扫描仪获得129个60~75岁的老年男性人体样本数据,分别通过形态分析和数值分析说明了老年男性腰臀部和青年男性的差异。进一步确定最佳聚类数,并利用K-means聚类法将老年男性腰臀部划分为4类。同时构建基于BP神经网络的体型预测模型,测试集总体识别率达到93.75%。结果显示,该方法可有效区分老年人体腰臀部形态差异,为制作合体性更高的老年男性裤装结构奠定了理论基础。
Body shape classification parameters are a key element of intelligent clothing production and the important premise of fine garment technology,and the establishment of body shape models is an important research topic in the current apparel industry.In order to analyze the problem of trouser suitability for the elderly to be solved urgently,129 human samples of 60~75 years old men were obtained through a three-dimensional body scanner.Through morphological analysis and numerical analysis,respectively,the difference between the waist and hips of the elderly and the young was explained,and the significance of the research was confirmed.Further it determined the optimal number of clusters,and used the K-means clustering method to divide the waist and hips of the elderly into 4 categories.On this basis,a body shape prediction model based on BP neural network was constructed,and the overall recognition rate of the test set reached 93.75%.The results show that this method can effectively distinguish the difference in the shape of the waist and hips of the elderly,which lays a theoretical foundation for the production of a more fit trouser structure for the elderly.
作者
曹晓梦
王春茹
罗斯祺
钟安华
Cao Xiaomeng;Wang Chunru;Luo Siqi;Zhong Anhua(School of Fashion,Wuhan Textile University,Wuhan,Hubei 430073,China;School of Fashion Engineering,Jiangxi Institute of Fashion Technology,Nanchang,Jiangxi 330201,China)
出处
《针织工业》
北大核心
2023年第7期76-80,共5页
Knitting Industries
基金
湖北省虚拟仿真试验室建设项目(D141091003)
湖北省大学生双创项目(S202010495025X)。
关键词
老年男性
腰臀部体型
体型分类
预测模型
神经网络
Elderly Men
Waist and Hip Body Shape
Body Shape Classification
Prediction Model
Neural Networks
作者简介
曹晓梦(1995-),女,硕士研究生。主要从事人体工学与服装数字化研究;通讯作者:钟安华(1967-),女,教授。E-mail:zhongah@yeah.net。
