Prediction of men's shirt pattern based on 3D body measurements

Abstract

Purpose The paper discusses the prediction of shirt patterns for different body sizes using multiple linear regression (MLR). Design/methodology/approach – A total of 29 pattern parameters from men's tailor‐made shirt and 34 body parameters obtained from a body scanner were designed for analysis. MLR has been applied to examine the underlying relationship between shirt pattern parameters and body measurements. Findings – Compared with formulae from the pattern expert, the prediction of shirt pattern from MLR has been improved. Originality/value – The findings could help to predict pattern size with different body sizes more accurately.