个性化
大规模定制
计算机科学
参数统计
聚类分析
服装
参数化模型
数据挖掘
人工智能
机器学习
万维网
数学
历史
统计
考古
作者
Qinwen Ye,Rong Huang,Huanhuan Liu,Zhaohui Wang
出处
期刊:AATCC journal of research
[American Association of Textile Chemists and Colorists - AATCC]
日期:2023-05-01
卷期号:10 (4): 250-262
标识
DOI:10.1177/24723444231161749
摘要
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.
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