Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (01): 125-132.doi: 10.13475/j.fzxb.20200707808

• Apparel Engineering • Previous Articles     Next Articles

3-D modeling of neck-shoulder part based on human photos

WANG Ting1, GU Bingfei1,2,3()   

  1. 1. School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    2. Clothing Engineering Research Center of Zhejiang Province, Hangzhou, Zhejiang 310018, China
    3. Key Laboratory of Silk Culture Heritage and Products Design Digital Technology, Ministry of Culture and Tourism, Hangzhou, Zhejiang 310018, China
  • Received:2020-07-30 Revised:2020-10-14 Online:2021-01-15 Published:2021-01-21
  • Contact: GU Bingfei E-mail:gubf@zstu.edu.cn

RichHTML

19

PDF (PC)

196

Abstract:

In order to facilitate personalized clothing online design and virtual fitting, a method of size extraction and 3-D modeling based on the front and side photographs of human body was proposed. Eight characteristic cross-sectional layers related to the neck-shoulder shape were determined based on 202 young women's 3-D point cloud data. Taking the center point of each cross-section layer as the reference point, the angle radius was measured every 10° and the relationship among the angle radius, the thickness and width of the curves were analyzed to establish the curve shape rules of each sectional layer. Then, the image segmentation technology was used to extract the human contour based on the front and side photos, the height area where the neck-shoulder feature points were located was identified through the height proportion of the human body, and the parameters required for the curve shape rules of each characteristic section were extracted with the neck-shoulder shape rules. Finally, according to the curve shape rules and anthropometric parameters, NURBS surface modeling was used to realize the 3-D model construction of neck and shoulder based on human body photos. The results show that the error percentage of the basic parameters extracted from human body photos is less than 5%, and the absolute error between the 3-D model constructed by this method and the real value is within 1 cm or 1°, which proves the feasibility of this method, and provides technical support for the automatic generation of garment pattern and 3-D virtual fitting.

Key words: neck-shoulder shape, human body photos, size extraction, virtual fitting, 3-D modeling

CLC Number: 

  • TS941.17

Tab.1

Basic size information of experimental objects"

参数 身高/cm 颈点高/cm 侧颈点高/cm 肩点高/cm 腋下点高/cm 颈围/cm 侧颈围/cm 肩围/cm 腋下围/cm
最小值 154.1 130.7 125.6 124.0 110.0 29.5 33.6 59.3 76.9
最大值 172.4 148.6 145.8 145.6 133.0 40.8 46.9 82.8 99.4
平均值 161.4 137.8 135.4 132.5 122.1 33.5 38.9 72.8 87.1
标准差 3.9 3.8 3.6 4.5 3.9 2.3 2.7 4.5 4.5
变异系数/% 2.4 2.8 2.7 3.4 3.2 6.9 6.9 6.2 5.2

Tab.2

Determination of sample size"

测量项目 样本均值xˉ/cm 标准差s/cm 样本量n
身高 161.43 3.93 23
颈围 33.54 2.27 176
肩围 72.76 4.45 144
腋下围 87.08 4.47 101

Fig.1

Schematic diagram of photo pose. (a)Front; (b)Side"

Fig.2

Determination of neck-shoulder section"

Fig.3

Schematic diagram of MER algorithm"

Fig.4

Measurement diagram of shoulder section curve"

Tab.3

Correlation analysis"

角度
半径		 肩厚 肩宽
r sig. r sig.
R0 0.970** 0.000 0.723** 0.000
R10 0.976** 0.000 0.743** 0.000
R20 0.979** 0.000 0.686** 0.000
R30 0.972** 0.000 0.682** 0.000
R40 0.897** 0.000 0.808** 0.000
R50 0.781** 0.000 0.851** 0.000
R60 0.631** 0.000 0.858** 0.000
R70 0.491** 0.005 0.855** 0.000
R80 0.343 0.050 0.843** 0.000
R90 0.672** 0.000 0.983** 0.000

Fig.5

Scatter plot of shoulder section R140"

Tab.4

Regression equation of shoulder section angle radius with thickness and width"

角度/(°) 回归方程 R2
0 R0=0.491D-0.481 0.941
10 R10=0.472D+3.040 0.953
20 R20=0.490D+3.467 0.959
30 R30=0.541D+0.293 0.944
40 R40=0.390D+0.092W-3.813 0.875
50 R50=0.228D+0.161W+2.987 0.793
60 R60=0.051D+0.287W-4.381 0.739
70 R70=-0.198D+0.475W-17.565 0.746
80 R80=-0.762D+0.830W-23.305 0.808
90 R90=0.501W-2.330 0.966

Fig.6

Front and side image processing. (a)Segmentation; (b)Filling holes and opening;(c) Extracted silhouette"

Tab.5

Definition of neck-shoulder dimensions"

高度 宽度 厚度
参数 符号 参数 符号 参数 符号
颈点高 HNP 颈宽 WNP 颈厚 DNP
侧颈点高 HSNP 侧颈宽 WSNP 侧颈厚 DSNP
肩点高 HSP 肩宽 WSP 肩厚 DSP
腋点高 HAP 腋下宽 WAP 腋下厚 DAP
身高 H

Fig.7

Measurement diagram of 2-D dimension extraction"

Fig.8

Measurement diagram of neck thickness"

Tab.6

2-D extraction error analysis"

指标 特征
部位		 成对差分(提取值-测量值) T值 显著性 相关
系数		 平均绝对
误差/cm		 误差
百分比/%
均值/cm 标准差/cm 标准误差
厚度 颈部 -0.086 1 0.367 7 0.058 1 -1.481 0.147 0.868 0.32 3.05
侧颈部 -0.115 7 0.427 7 0.067 6 -1.710 0.095 0.877 0.37 3.55
肩部 -0.068 6 0.493 6 0.078 0 -0.879 0.385 0.908 0.43 3.46
腋下 -0.267 0 0.877 5 0.138 7 -1.924 0.062 0.847 0.75 3.78
宽度 颈部 -0.022 2 0.400 8 0.063 4 -0.351 0.728 0.859 0.34 3.24
侧颈部 -0.053 2 0.489 0 0.077 3 -0.689 0.495 0.861 0.43 3.20
肩部 0.059 9 0.788 9 0.124 7 0.480 0.634 0.910 0.66 2.12
腋下 0.050 4 0.597 8 0.094 5 0.005 3 0.597 0.964 0.51 1.62

Fig.9

Diagram of center adjustment"

Fig.10

Neck-shoulder model of sample. (a) Sample 1#; (b) Sample 2#"

Tab.7

Allowable error of specification"

服装类型 误差/cm
颈围 肩宽 胸围
西服 ±0.6 ±0.6 ±2.0
衬衫 ±0.6 ±0.8 ±2.0
连衣裙 ±0.6 ±0.8 ±2.0

Tab.8

3-D modeling error analysis"

样
本		 部位 肩斜
角/(°)		 背入
角/(°)		 颈厚/
cm		 颈宽/
cm		 侧颈厚/
cm		 侧颈宽/
cm		 肩厚/
cm		 肩宽/
cm		 腋下厚/
cm		 腋下宽/
cm		 颈围/
cm		 侧颈围/
cm		 肩围/
cm		 腋下围/
cm
1# 模型
尺寸		 23.5 17.8 11.6 12.4 12.0 15.5 12.5 33.8 20.8 33.6 37.7 43.7 76.9 90.9
三维测
量尺寸		 22.6 17.9 11.9 12.1 12.0 15.6 12.9 33.8 20.6 33.8 38.2 44.3 77.9 91.6
误差 -0.9 0.1 0.3 -0.3 0.0 0.1 0.4 0.0 -0.2 0.2 0.5 0.6 1.0 0.7
2# 模型
尺寸		 24.2 12.9 10.0 10.6 10.5 13.6 13.3 30.7 20.2 30.1 32.1 38.2 71.3 84.9
三维测
量尺寸		 24.9 12.8 10.2 11.0 10.4 13.8 13.5 30.9 20.4 30.2 32.0 38.3 71.7 85.2
误差 0.7 -0.1 0.2 0.4 -0.1 0.2 0.2 0.2 0.2 0.1 -0.1 0.1 0.4 0.3
[1] CHENG Z Q, CHEN Y, MARTIN R R, et al. Parametric modeling of 3D human body shape-A survey[J]. Computers & Graphics, 2018,71:88-100.
[2] PISHCHULIN L, WUHRER S, HELTEN T, et al. Building statistical shape spaces for 3D human modeling[J]. Pattern Recognition, 2017,67:276-286.
[3] HEEKYUNG J, CHEN J. A study on 3D virtual body formation and deformation by body shape analysis[J]. International Journal of Clothing Science and Technology, 2019,31(6):755-776.
[4] LI J, YU Q, XU H, et al. Measuring and modeling human bodies with a novel relocatable mechatronic sensor-net[J]. Textile Research Journal, 2019,89(19/20):4131-4147.
[5] SHIN J Y, Nam Y J. A study on body shape for 3D virtual body shape transformation-focusing on the women with age of forties[J]. Fashion & Textile Research Journal, 2015,17(2):265-277.
[6] MARKIEWICZ Ł, WITKOWSKI M, SITNIK R, et al. 3D anthropometric algorithms for the estimation of measurements required for specialized garment design[J]. Expert Systems With Application, 2017,85(1):366-385.
[7] AFFUSO O, PRADHAN L, ZHANG C, et al. A method for measuring human body composition using digital images[J]. PLoS ONE, 2018,13(11):1-13.
[8] 许明星, 李重. 基于图像的人体特征点提取与尺寸测量[J]. 计算机系统应用, 2018,27(6):87-94.
XU Mingxing, LI Zhong. Image-based feature extraction and dimension measurement for human bodies[J]. Computer Systems & Applications, 2018,27(6):87-94.
[9] SENANAYAKE M, RAHEJA A, ZHANG Y H. Automated human body measurement extraction[J]. International Journal of Clothing Science & Technology, 2018,30(2):175-194.
[10] 马黎. 基于图像的非接触式人体测量算法的研究与实现[D]. 成都: 电子科技大学, 2017: 36-47.
MA Li. Research and implementation of non-contacting anthropometric algorithm based on image[D]. Chengdu: University of Electronic Science and Technology of China, 2017: 36-47.
[11] 胡新荣, 刘嘉文, 刘军平, 等. 基于ABSS的着装人体多特征点提取与尺寸测量[EB/OL]. 计算机工程, 2020: 1-10.[2020-01-10]. http://kns.cnki.net/kcms/detail/31.1289.tp.20200110.1329.004.html.
HU Xinrong, LIU Jiawen, LIU Junping, et al. Multi-features extraction and dimension measurement for dressed human bodies via adaptive body structure segmentation[EB/OL]. Computer Engineering, 2020: 1-10.[2020-01-10]. http://kns.cnki.net/kcms/detail/31.1289.tp.20200110.1329.004.html.
[12] CHEN G, LI J, ZENG J, et al. Optimizing human model reconstruction from RGB-D images based on skin detection[J]. Virtual Reality, 2016,20(3):159-172.
[13] 董鹏辉, 柯良军. 基于图像的三维重建技术综述[J]. 无线电通信技术, 2019,45(2):115-119.
DONG Penghui, KE Liangjun. Overview of 3D reconstruction techniques based on images[J]. Radio Communications Technology, 2019,45(2):115-119.
[14] 师乐. 基于二维图像实时个性化人体模型重建算法的研究[D]. 西安: 西安工程大学, 2019: 25-40.
SHI Le. Research on real-time personalized human body model reconstruction algorithm based on two-dimensional image[D]. Xi'an: Xi'an Polytechnic University, 2019: 25-40.
[15] 王力. 基于图像的非接触式人体测量与建模技术研究[D]. 西安:西安工程大学, 2018: 27-51.
WANG Li. Research on non-contacting human body measurement and modeling technology based on image[D]. Xi'an: Xi'an Polytechnic University, 2018: 27-51.
[16] 王永波. 基于3D人体测量的江浙地区青年男性腰臀部特征研究[D]. 无锡: 江南大学, 2019: 12-13.
WANG Yongbo. Study on characteristics of Jiangsu and Zhejiang young male's waist-hip based on 3D Body measurement[D]. Wuxi: Jiangnan University, 2019: 12-13.
[17] 贺莉文. 基于肩截面曲线的弓背型青年男体细分与识别模型[D]. 苏州: 苏州大学, 2018: 38-39.
HE Liwen. Classification and recognition model of the hunchback young male body based on shoulder section curve[D]. Suzhou: Soochow University, 2018: 38-39.
[18] 余张君. 基于中老年着装人体美评价的旗袍用人台建模研究[D]. 上海: 东华大学, 2018: 40-42.
YU Zhangjun. Research on cheongsam mannequin modeling based on the evaluation of physical beauty in middle-aged and elderly group[D]. Shanghai: Donghua University, 2018: 40-42.
[19] 王兴晨, 路春光, 赵震, 等. 逆向工程特征点提取与参数化建模方法研究[J]. 机械设计与制造, 2018,323(1):222-225.
WANG Xingchen, LU Chunguang, ZHAO Zhen, et al. Research on extraction from reverse engineering characteristics section and parameterized modeling method[J]. Machinery Design & Manufacture, 2018,323(1):222-225.
[1] WANG Ting, GU Bingfei. Automatic identification of young women′s neck-shoulder shapes based on images [J]. Journal of Textile Research, 2020, 41(12): 111-117.
[2] CHEN Mi, YE Qinwen, ZHANG Gaopeng. Construction of parametric structure model for bias-cut skirt pattern [J]. Journal of Textile Research, 2020, 41(07): 135-140.
[3] XU Qian, CHEN Minzhi. Garment grain balance evaluation system based on deep learning [J]. Journal of Textile Research, 2019, 40(10): 191-195.
[4] WANG Xu, CHU Changliu, NI Qingqing, LIU Xinhua. Three-dimensional modeling on single-layer woven fabric structure using MAXScript language [J]. Journal of Textile Research, 2019, 40(01): 159-165.
[5] . Computer simulation and system realization of 3-D weft knitted jacquard fabric [J]. JOURNAL OF TEXTILE RESEARCH, 2016, 37(07): 155-161.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备14006648号
Copyright 2021 © Editorial office of Journal of Textile Research
Supported by Beijing Magtech Co.Ltd