Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (12): 151-159.doi: 10.13475/j.fzxb.20211003609

• Apparel Engineering • Previous Articles     Next Articles

Shirt pattern generating method based on 3-D human scanning model

XIAO Boxiang, LIU Zhengdong(), GUO Yucheng, WANG Yuanxia   

  1. School of Fashion, Beijing Institute of Fashion Technology, Beijing 100029, China
  • Received:2021-10-19 Revised:2022-07-28 Online:2022-12-15 Published:2023-01-06
  • Contact: LIU Zhengdong E-mail:jsjlzd@bift.edu.cn

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Abstract:

Aiming at uncontrollable matching error between automatically generated pattern and body shape in shirt customization, an automatic generating method based on 3-D human body scanning model is proposed. The personalized 3-D human model was obtained by scanning the target human body, and the personalized body feature points were extracted on the 3-D human model by analyzing the geometric characteristics of the cross-section curves of the model. A standard 3-D basic model of a shirt was constructed by using the standard mannequin for garment pattern making, and as-rigid-as possible (ARAP) deformation algorithm was used to create the deformation of the standard 3-D basic model with the personalized body feature points as constraints. Finally, using a 3-D model flattening algorithm based on the mass-spring system, the corresponding 2-D pattern was generated according to the deformed 3-D clothing models, and offsets of the edge lines of the pattern verified by experiments were considered in generating the final personalized shirt pattern that adapts to the target body shape. The experimental results show that this method can generate shirt pattern with good fitting. Based on the digital model and automatic processing algorithm, automatic generation of shirt pattern can be achieved that ensures the accuracy and improves the efficiency of personalized pattern making. The research outcome provides a technical solution for garment intelligent manufacturing.

Key words: garment CAD, 3-D human body scanning, men's shirt, pattern generating, mass-spring system, customized garment

CLC Number: 

  • TS941.26

Fig.1

Flowchart of proposed method"

Fig.2

3-D human body scanning device (a) and scanned model sample (b)"

Fig.3

Scanned 3-D human body model analysis and extraction of feature points, curves, intersections. (a) Scanned model; (b) Intersection curves; (c) Feature curves on body; (d) Feature points"

Fig.4

3-D base shape model of cloth. (a) Triangle surface model; (b) Mesh structure with key curves"

Fig.5

3-D cloth model deformation by constrains of feature points. (a) Source model and feature points; (b) Comparison of source and aim points set; (c) Aim model and feature points"

Fig.6

3-D shape flatten via physics-based model"

Fig.7

Flatten of left-front piece and internal energy distribution. (a)3-D piece;(b)2-D piece; (c)Energy distribution"

Fig.8

Edge curves on left-front piece. (a)3-D piece; (b)Front-middle curve;(c)Collar curve;(d)Shoulder curve;(e)Sleeve hole curve; (f)Side edge curve; (g)Bottom edge curve"

Tab.1

Deformation comparison between 2-D and 3-D shapes"

参数 前中/
mm		 领/
mm		 肩/
mm		 袖窿/
mm		 侧缝/
mm		 底边/
mm		 面积/
mm2
三维
长度		 657.0 122.3 135.1 195.9 531.2 219.2 144 339
二维
长度		 652.8 122.1 135.3 196.6 528.3 219.6 144 353
变形率/% -0.64 -0.15 0.17 0.37 -0.53 0.18 0.01

Fig.9

Flatten of front, back and shoulder for shirt patterns. (a)3-D piece; (b)2-D piece; (c)2-D pattern"

Fig.10

Deformation of edge curves of front, back and shoulder pieces, and generated collar and sleeve pieces"

Tab.2

Offset values and direction of key points on edge curves of pattern"

版片特征点 偏移值/cm 偏移方式
前肩点 1 沿肩线延伸
前胸侧点 3 偏移x坐标值
-1 偏移y坐标值
前底侧点 3 偏移x坐标值
-1 偏移y坐标值
后肩点 1 沿肩线延伸
后背侧点 1 沿横向延伸
后胸侧点 3 偏移x坐标值
-1 偏移y坐标值
后底侧点 3 偏移x坐标值
-1 偏移y坐标值

Tab.3

Comparison of main measurement parameters for fitting evaluation of patterncm"

项目 胸围 领围 肩宽 衣长 袖长
人体手工量体尺寸 89 40 45 64 53
三维模型测量尺寸 88 40 44 56 54
手工制版加放松量 13 2 2 0 3
本文方法加放松量 12 0 2 10 3
本文样衣实测尺寸 100 41 43 66 57

Fig.11

Results of clothing try on real human body. (a) Front view; (b) Side view; (c) Back view; (d) Action of arm rising up; (e) Action of arm back; (f) Action of arm front"

Tab.4

Geometric information of models and processing time of system modulus"

算法与处理流程 运行时间/s
体型特征点分析
(31个体型特征点,三维人体模型约93 800
个顶点,171 000个三角面)		 22
三维模型保刚性变形
(三维模型1 177个顶点,2 232个三角面)		 12
三维版型展平(迭代10 000次)
(肩片50个顶点,72个三角面)		 3
三维版型展平(迭代10 000次)
(后片120个顶点,198个三角面)		 5
三维版型展平(迭代10 000次)
(前片310个顶点,531个三角面)		 9
二维版型后处理 1
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