纺织学报 ›› 2020, Vol. 41 ›› Issue (12): 111-117.doi: 10.13475/j.fzxb.20200502607

• 服装工程 • 上一篇    下一篇

基于二维图像的青年女性颈肩部形态自动识别

王婷1, 顾冰菲1,2,3()   

  1. 1.浙江理工大学 服装学院, 浙江 杭州 310018
    2.浙江省服装工程技术研究中心, 浙江 杭州 310018
    3.丝绸文化传承与产品设计数字化技术文化和旅游部重点实验室, 浙江 杭州 310018
  • 收稿日期:2020-05-13 修回日期:2020-08-31 出版日期:2020-12-15 发布日期:2020-12-23
  • 通讯作者: 顾冰菲
  • 作者简介:王婷(1995—),女,硕士生。主要研究方向为数字化服装技术。
  • 基金资助:
    国家自然科学基金项目(61702461);国家自然科学基金项目(61702460);中国纺织工业联合会科技指导性项目(2018079);中国纺织工业联合会应用基础研究项目(J202007);浙江理工大学科研业务费专项资金资助项目(2020Q051);浙江理工大学服装服饰文化创新团队项目(11310031282006)

Automatic identification of young women's neck-shoulder shapes based on images

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 Inheriting and Products Design Digital Technology, Ministry of Culture and Tourism, Hangzhou, Zhejiang 310018, China
  • Received:2020-05-13 Revised:2020-08-31 Online:2020-12-15 Published:2020-12-23
  • Contact: GU Bingfei

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摘要：

为实现青年女性颈肩部形态的自动识别,首先基于202名在校青年女性的三维点云数据,测量了15个颈肩部形态相关参数,通过分析确定出离散程度较大的形态参数,包括肩斜角、背入角、肩矢额径比和腋下矢额径比;然后结合这4个重要体型参数,对青年女性颈肩部形态进行细分并建立各类体型的分类规则;最后基于青年女性正面与侧面二维照片,通过提取人体轮廓和识别特征点获得颈肩部体型分类所需参数,根据体型分类规则实现颈肩部形态的自动识别。结果表明:青年女性颈肩部形态可分为4类,即圆宽肩体、扁窄肩体、圆落肩体、驼背扁肩体,分别占样本总数的25.53%、23.94%、25.59%和23.94%;通过对40名测试样本进行基于正、侧面二维照片的颈肩部形态自动识别验证,准确率达到90%,说明基于本文方法构建的颈肩部体型自动识别系统是有效的。

关键词: 颈肩部形态, 体型分类, 图像, 尺寸提取, 自动识别

Abstract:

In order to facilitate the automatic identification of young women's neck-shoulder shapes, 15 neck-shoulder shape parameters of 202 young women were measured in the form of three-dimensional point cloud data, and the parameters with a large degree of dispersion were determined through analysis, including the shoulder angle, back angle, shoulder depth/width ratio and armpit depth/width ratio. Combined with these four important body parameters, the neck-shoulder shape of young women was classified following the established classification rules. Based on the front and side images, the parameters required for neck-shoulder shape classification were obtained by extracting the human body contour and identifying the feature points, and the automatic identification of the neck-shoulder shape was achieved according to the body type classification rules. The results show that young women's neck-shoulder shape is divided into four categories, namely round wide shoulder, flat narrow shoulder, round drop shoulder, hunchback flat shoulder, accounting for 25.53%, 23.94%, 25.59% and 23.94%, respectively, of the total sample. The identification of the neck-shoulder shape based on the front and side images of 40 test samples is verified, and the accuracy ratio reaches 90%, indicating that the neck-shoulder shape automatic identification system constructed using this method is effective.

Key words: neck-shoulder shape, body classification, image, size extraction, automatic identification

中图分类号: 

  • TS941.17

表1

颈肩部形态参数测量和计算"

序号 指标 测量与计算方法 序号 指标 测量与计算方法
1 身高(H) 头顶点至地面的垂直距离 8 颈高比(RhNP) 颈点高(HNP)/身高(H)
2 颈点高(HNP) 侧面头部与颈部交接点至地面的垂直距离 9 侧颈高比(RhSNP) 侧颈点高(HSNP)/身高(H)
3 侧颈点高(HSNP) 正面颈与肩交接点至地面的垂直距离 10 肩高比(RhSP) 肩点高(HSP)/身高(H)
4 肩点高(HSP) 肩端点至地面的垂直距离 11 腋高比(RhAP) 腋点高(HAP)/身高(H)
5 前腋点高(HAP) 手臂与胸部交接点至地面的垂直距离 12 颈矢额径比(RNP) 颈厚(DNP)/颈宽(WNP)
6 肩斜角(AST) 侧颈点和肩端点连线与水平面形成的夹角 13 侧颈矢额径比(RSNP) 侧颈厚(DSNP)/侧颈宽(WSNP)
7 背入角(ADE) 侧面背部最突出的点和颈点的连线
与垂直面形成的夹角		 14 肩矢额径比(RSP) 肩厚(DSP)/肩宽(WSP)
15 腋下矢额径比(RAP) 腋下厚(DAP)/腋下宽(WAP)

图1

颈肩部形态参数测量方法"

图2

正态P-P图"

表2

相关变量描述统计分析表"

变量描述 身高/
cm		 颈点
高/cm		 侧颈点
高/cm		 肩点高/
cm		 前腋点
高/cm		 肩斜角/
(°)		 背入角/
(°)		 颈矢额
径比		 侧颈
矢额径比		 肩矢额
径比		 腋下
矢额径比
最小值 151.1 128.5 125.6 122.9 110.0 15.9 11.1 0.80 0.61 0.31 0.51
最大值 175.0 150.5 148.5 149.2 136.3 32.0 28.9 1.20 0.99 0.51 0.82
平均值 161.5 137.8 135.4 132.7 122.2 25.1 17.7 0.99 0.78 0.41 0.66
标准差 4.6 4.3 4.1 5.0 4.5 3.1 3.5 0.08 0.06 0.04 0.07
变异系数/% 2.848 3.120 3.028 3.768 3.682 12.351 20.468 8.081 7.692 9.756 10.606

表3

最终聚类中心"

体型
分类		 肩斜角/
(°)		 背入角/
(°)		 肩矢额
径比		 腋下矢
额径比		 人数
a 24.0 16.5 0.42 0.72 48
b 23.2 15.7 0.37 0.61 45
c 28.7 16.6 0.45 0.68 50
d 24.4 21.9 0.41 0.62 45

图3

4类体型横截面形态"

表4

4类颈肩部体型分类规则"

体型
分类		 肩斜
角/(°)		 背入
角/(°)		 肩矢额
径比		 腋下矢
额径比
a 19~27
(不含27)		 13~19
(不含19)		 0.38~0.46 0.66~0.82
b 16~26 11~18 0.31~0.41 0.51~0.66
(不含0.66)
c 27~32 13~21 0.40~0.51 0.58~0.77
d 19~27
(不含27)		 19~29 0.36~0.46 0.54~0.69

表5

判别准确性分析"

体型
分类		 预测的群成员分类 总计 判别准
确率/%
a b c d
a 46 0 2 0 48 95.8
b 1 44 0 0 45 97.8
c 3 0 46 1 50 92.0
d 0 1 0 44 45 97.8

图4

校准示意图"

图5

拍摄姿势示意图"

图6

正侧面图像处理过程"

图7

颈点确定示意图"

图8

肩斜角计算示意图"

图9

本文分类规则对颈肩部识别结果"

表6

特征形态参数提取误差分析"

变量 类型 均值 标准差 相关系数 平均绝对误差 误差范围
肩斜角 提取值 25.296° 2.405 0° 0.955 0.63° -1.3°~1.4°
测量值 25.336° 2.451 6°
背入角 提取值 18.201° 2.167 2° 0.891 0.96° -1.5°~1.7°
测量值 18.130° 2.422 6°
肩矢额径比 提取值 0.406 2 0.455 3 0.927 0.01 -0.02~0.02
测量值 0.410 9 0.255 5
腋下矢额径比 提取值 0.642 0 0.563 3 0.776 0.03 -0.07~0.06
测量值 0.630 0 0.555 6

表7

特征形态参数配对样本T检验结果"

变量 均值 标准差 标准误差 T值 显著性
肩斜角 -0.040 0.727 0.115 -0.352 0.727
背入角 0.705 1.102 0.174 0.405 0.688
肩矢额径比 -0.005 0.024 0.004 -1.249 0.219
腋下矢额径比 0.011 0.047 0.008 1.438 0.158
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