{"title":"A novel evaluation method of Chinese female lower body shapes based on machine learning","authors":"Xiaofeng Yao, Jinzhu Shen, Jianping Wang","doi":"10.1108/ijcst-08-2023-0125","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>The purpose of this paper is to define the evaluation criteria for Chinese female lower body shapes and simplify the evaluation process of shapewear, including girdles, shaping pants, etc.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The study utilized a machine learning algorithm based on support vector regression and optimized by a genetic algorithm to construct an evaluation model for the contour beauty of Chinese female lower body shapes. A total of 64 virtual 3D models of women were measured. These models were rated by 42 raters using the Likert 9 psychological scale and data was obtained from 310 female samples.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Eight factors were selected and used to create a regression prediction model. The model achieved an accuracy of 84.7% for the training samples and 86.6% for the test samples.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The model can be utilized to assess the aesthetic appeal of the female lower body and to evaluate the shaping impact of shapewear. The research and evaluation of shapewear for the female lower body are of great significance, particularly in enhancing production efficiency.</p><!--/ Abstract__block -->","PeriodicalId":50330,"journal":{"name":"International Journal of Clothing Science and Technology","volume":"13 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Clothing Science and Technology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1108/ijcst-08-2023-0125","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, TEXTILES","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
The purpose of this paper is to define the evaluation criteria for Chinese female lower body shapes and simplify the evaluation process of shapewear, including girdles, shaping pants, etc.
Design/methodology/approach
The study utilized a machine learning algorithm based on support vector regression and optimized by a genetic algorithm to construct an evaluation model for the contour beauty of Chinese female lower body shapes. A total of 64 virtual 3D models of women were measured. These models were rated by 42 raters using the Likert 9 psychological scale and data was obtained from 310 female samples.
Findings
Eight factors were selected and used to create a regression prediction model. The model achieved an accuracy of 84.7% for the training samples and 86.6% for the test samples.
Originality/value
The model can be utilized to assess the aesthetic appeal of the female lower body and to evaluate the shaping impact of shapewear. The research and evaluation of shapewear for the female lower body are of great significance, particularly in enhancing production efficiency.
期刊介绍:
Addresses all aspects of the science and technology of clothing-objective measurement techniques, control of fibre and fabric, CAD systems, product testing, sewing, weaving and knitting, inspection systems, drape and finishing, etc. Academic and industrial research findings are published after a stringent review has taken place.