Predicting detailed body sizes by feature parameters
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 27 May 2014
Abstract
Purpose
Detailed body sizes are prerequisite for made to measure or customized manufacture. Nowadays, detailed body sizes can be precisely obtained by using 3D scanners, however, the high prices of the scanners block the population for such approaches. The purpose of this paper is to provide an economical and accurate data-driven method which can predict detailed body sizes with a small number of feature sizes.
Design/methodology/approach
First, the representative body sizes are extracted from dozens of detail body sizes by using factor analysis and garment knowledge. Among the representative body sizes, those that are easy to be measured are selected as the feature parameters (FPs). Second, by mining the database of the body sizes, mapping from the FPs to the detailed body sizes is expressed by a combination of radial basis function and multiply linear regression. Thus, for an individual human body, his/her detailed body sizes can be predicted by a small number of FPs.
Findings
First, FPs which are easily measured and represent the main shape information of a human body are extracted. Second, detailed body sizes can be functionally predicted by the FPs.
Originality/value
Traditionally, measuring dozens of body sizes for each human body is tiresome and the accuracy of the sizes depends on the experience of the gaugers. In this paper, a small number of body sizes are selected as the FPs which are easy to be measured and can functionally express the other body sizes. Thus, by only measuring the FPs, the detailed body sizes can be intelligently and automatically predicted. This approach is meaningful to improve the intelligence and accuracy of the measurement, so that even an inexperienced gauger is competent to obtain accurate detailed body sizes.
Keywords
Acknowledgements
This work was supported by the National Natural Science Foundation of China (NSFC, Nos 60903145, 61103106), the doctoral program of the Ministry of Education of China (20100101110025), the Fundamental Research Funds for the Central Universities (2012QNA4003), and Zhejiang Provincial Natural Science Foundation of China (No. Y1110230).
Citation
Liu, Z., Li, J., Chen, G. and Lu, G. (2014), "Predicting detailed body sizes by feature parameters", International Journal of Clothing Science and Technology, Vol. 26 No. 2, pp. 118-130. https://doi.org/10.1108/IJCST-02-2013-0009
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited