Individualized Garment Pattern Generation in Batches Based on Biarc and Ezdxf

Abstract

With the stimulating demand of consumers for personalized garments, mass customization is gradually becoming prevalent. However, the automatic generation of personalized garment patterns remains core to mass customization. In this article, we propose a novel parametric apparel pattern-making method and achieve the automatic generation of personalized garment patterns in batches. First, we review the basic principle of biarc and present a new parametric pattern-making method based on biarc and ezdxf. Second, 1000 3D human models randomly generated by the SMPL-X parametric human model are clustered into 10 classes with the k-means clustering method, and 10 representative human models are selected from each cluster to generate their personalized garment pattern. Finally, the rationality of the personalized garment pattern is verified by virtual fitting. Our method has several advantages: (1) the proposed parametric biarc can be easily used to build parametric garment patterns without being limited by the style of the garment, (2) the proposed method is capable of generating personalized garment patterns in batches by imputing measurements from large numbers of individuals, and it only takes very little time, and (3) the personalized garment patterns can fit human bodies very well. The proposed method can be used to build parametric garment patterns and to achieve the batch generation of personalized patterns, improving the efficiency of garment customization and the quality of final products.