纺织学报 ›› 2019, Vol. 40 ›› Issue (01): 120-129.doi: 10.13475/j.fzxb.20180306210

• 服装工程 • 上一篇    下一篇

基于散乱点云的三维人体自动测量

鲍陈1, 缪永伟2(), 孙瑜亮1, 张旭东1   

  1. 1.浙江工业大学 计算机科学与技术学院, 浙江 杭州 310023
    2.浙江理工大学 信息学院, 浙江 杭州 310018
  • 收稿日期:2018-03-26 修回日期:2018-10-03 出版日期:2019-01-15 发布日期:2019-01-18
  • 通讯作者: 缪永伟
  • 作者简介:鲍陈(1983—),男,博士生。主要研究方向为计算机图形学、服装数字化技术。
  • 基金资助:
    国家自然科学基金项目(61272309);浙江理工大学科研基金项目(17032001-Y)

Automatic measurement of three-dimensional human body based on scattered point cloud

BAO Chen1, MIAO Yongwei2(), SUN Yuliang1, ZHANG Xudong1   

  1. 1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
    2. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
  • Received:2018-03-26 Revised:2018-10-03 Online:2019-01-15 Published:2019-01-18
  • Contact: MIAO Yongwei

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摘要：

为解决Kinect深度相机三维人体扫描重建中人体特征尺寸提取的问题,提出一种基于散乱点云的三维人体自动测量方案。首先,对采集三维点云数据进行预处理,经点云降采样、离群点滤波和表面重建,以及点云坐标转换,进而识别出人体正背面;然后,利用人体几何形状分析法,自动提取人体特征点和特征截面点云;最后,对得到的特征截面点云提取特征边界点,再通过基于凸壳的轮廓线提取算法得到特征边界线,通过三次B样条曲线拟合计算围度、弧长尺寸,利用坐标差值和欧氏距离计算长度尺寸,从而完成对三维人体点云模型的特征尺寸测量。结果表明,该方案受人体体型因素影响较小,所提出的尺寸信息的自动提取方案有效,并符合相关标准中测量精度的要求。

关键词: 散乱点云, 点云分割, 人体特征点, 三维人体测量

Abstract:

In order to solve the human body's characteristic size extraction in 3-D human body scanning reconstruction using Kinect depth camera, an automatic measurement scheme of 3-D human body size based on scattered point cloud was proposed. Firstly, the collected 3-D point cloud was preprocessed, and then the front and back surfaces of a human body were identified by point cloud desampling, outlier filtering, surface reconstruction and point cloud coordinate transformation. Then, the human body geometric shape analysis method was used to automatically extract human body's characteristic points and characteristic section point cloud. Finally, the characteristic boundary points were extracted from the obtained characteristic cross section point cloud, and then the characteristic boundary line was obtained by the contour extraction algorithm based on the convex hull, the girth and arc length were calculated through the cubic B-spline curve fittings, and the length was calculated by coordinate difference and Euclidean distance, so that the characteristic size measurement of the 3-D human body point cloud model was completed. The experiment results show that the scheme is less affected by human body shape factors, and the proposed automatic extraction scheme of size information is effective. The feasibility is verified according to the measurement accuracy requirements of related standard.

Key words: scattered point cloud, point cloud segmentation, characteristic point of human body, 3-D human body measurement

中图分类号: 

  • TS941.26

图1

人体尺寸测量系统装置"

图2

人体尺寸测量流程图"

图3

人体点云数据预处理 (a)Original point cloud; (b)Point cloud desampling, denoising, and surface reconstruction; (c)Point cloud coordinate transformation"

表1

人体特征点位置与身高之间比例"

特征点名称 特征点位置与身高的比例
男 女
头顶点 1.00 1.00
颈侧点 0.84 0.86
肩峰点 0.82 0.81
腋窝点 0.75 0.75
胸高点 0.72 0.72
腰侧点 0.61 0.63
臀凸点 0.53 0.53
会阴点 0.47 0.47
膝盖点 0.26 0.28
外踝点 0.05 0.05
脚点 0.00 0.00

图4

人体点云分割结果示意图 (a)Human body segmentation key points; (b) Human body segmentation result"

图5

颈根围线提取 (a)Oblique cross section neck base line; (b) Neck base line rotaled by 20°"

图6

判别边界特征点 (a)P is boundary point;(b)P is interior point"

图7

胸围凸包B样条拟合 (a)Chest circumference characteristic boundary line; (b)Chest circumference convex-hull fitting curve"

图8

腰围凸包B样条拟合 (a)Waist circumference characteristic boundary line; (b)Waist circumference convex-hull fitting curve"

图9

背宽凸包B样条拟合 (a)Back breadth characteristic boundary line; (b) Back breadth convex-hull fitting curve"

图10

交互测量界面"

表2

测量结果精密度分析"

测量
项目		 观察者(i) 均值 IQR 标准差 CV值/%
第1次 第2次 第3次 第4次 第5次
身高 169.06 168.97 169.17 169.42 168.82 169.09 0.20 0.225 544 0.13
胸围 87.83 87.96 88.14 87.72 88.32 87.99 0.31 0.240 167 0.27
腰围 79.02 79.14 79.17 78.80 79.46 79.12 0.15 0.240 250 0.30
臀围 93.09 93.16 93.26 92.43 92.81 92.95 0.35 0.335 336 0.36
肩宽 44.79 44.57 44.12 43.76 43.33 44.11 0.81 0.592 647 1.34
臂长 59.12 59.30 59.48 59.51 58.61 59.20 0.36 0.367 056 0.62
上身长 69.86 69.62 69.98 69.57 69.63 69.73 0.24 0.178 241 0.26
腿内侧长 75.12 75.06 74.77 74.92 74.86 74.95 0.20 0.143 457 0.19

图11

人体尺寸测量项目"

表3

测量的误差分析"

测量
项目		 本文方案
最大误差		 本文方案
最小误差		 本文方案
平均误差		 文献[4]
最大误差		 文献[18]
最大误差
身高 0.36 0.15 0.08 1.7
胸围 0.80 0.11 0.42 1.6 1.88
腰围 0.75 0.24 0.47 2.5 1.25
臀围 0.67 0.09 0.39 0.7 1.65
肩宽 0.85 0.31 0.78 1.6
臂长 0.38 0.1 0.21

图12

测量误差箱线图"

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