基于SVM的青年女子体型分类研究  

Research on the Young Women's Body Classification Based on SVM

作　　者：张苏豫[1] 邹奉元[1] 丁笑君[1] 池金米[1] 

机构地区：[1]浙江理工大学服装学院,杭州310018

出　　处：《浙江理工大学学报（自然科学版）》2008年第1期41-45,共5页Journal of Zhejiang Sci-Tech University(Natural Sciences)

基　　金：浙江省人事厅资助项目(0402248-M)

摘　　要：采用美国[TC]2公司的三维人体测量仪测得的江浙青年女性的人体数据,然后根据身体4个部位的形态特征,将人体数据细分为各种女性人体体型。在分类过程中,通过引入支持向量机(SVM)方法,提出了基于SVM的青年女子体型分类模型。结果表明,SVM方法的分类时间短,分类精度高,是一种有效的识别分类方法。Young women＇s data in Jiangsu and Zhejiang areas are acquired by using 3D Body Scanner made by American TC^2. Then according to the four parts of body shape character, human data can be classified into different kinds of women＇s body types. ＂In the process, SVM（support vector machine） model is used to identify the young women＇s shape. The results show that SVM is an effective identified and classified method due to short time and high precision. The reference data can be provided for the garment pattern design of young women＇s apparel.

关 键 词：支持向量机 三维测量 体型分类 青年女子体型 

分 类 号：TS941[轻工技术与工程—服装设计与工程]