摘要
人体体型是进行服装及相关产品研发和应用的前提和基础,研究前期对407名年龄在20-35周岁的中国东部地区青年女性进行了人体数据获取,并利用分层聚类法将人体分为14类并进行检验。从体型的应用角度出发,构建了以身腰比、胸腰差和臀腰差作为输入层节点,各体型类别为输出层节点的类神经网络体型判别模型。经检验,分类体型训练准确度均达到100.0%,测试准确度除两类外均达到100.0%,实现了基于类神经网络的人体体型识别。
Somatotype is the basis of garment and related products research.In the earlier stage of project,407 eastern China young women aged 20-35 were anthropometric measured.The 14 types somatotypes were obtained by two-step clustering analysis,and then were tested.Considering the application of the somatotypes,the Artificial Neural Network(ANN)was used to establish the discrimination model of somatotypes,which the input layer nodes were the ratio of heightwaist,chest-waist difference and hip-waist difference,and the output layer nodes were the various somatotypes.Through the evaluation,the training accuracy of samples reached 100%,and the testing accuracy of samples reached 100%except two types.The discrimination of young women’s somatotype based on Artificial Neural Network was achieved.
作者
李健
余佳佳
Li Jian;Yu Jiajia
出处
《服装设计师》
2020年第8期70-75,共6页
Fashion China
基金
服装工效及功能创新设计北京市重点实验室项目(KYTG02170202)
北京市教委项目(KM201910012012)。
关键词
类神经网络
体型
青年女性
乳下围矢径比
判别
Artificial Neural Network(ANN)
somatotype
young women
Discrimination
