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新型人体参数自动测量系统
引用本文:徐慧明,夏立坤,杨琪,刘宇杰,唐宋元,杨健. 新型人体参数自动测量系统[J]. 中国图象图形学报, 2017, 22(2): 225-231
作者姓名:徐慧明  夏立坤  杨琪  刘宇杰  唐宋元  杨健
作者单位:北京理工大学光电学院, 北京 100081,北京理工大学光电学院, 北京 100081,北京理工大学光电学院, 北京 100081,北京理工大学光电学院, 北京 100081,北京理工大学光电学院, 北京 100081,北京理工大学光电学院, 北京 100081
基金项目:国家自然科学基金项目(61572076);中国博士后科学基金项目(2015M570940);北京理工大学基础研究基金项目(20150442009)
摘    要:目的 针对国内外已有的非接触式测量系统普遍存在价格昂贵、安装复杂、占用空间大等问题,提出一种基于消失点和图像比例法相结合的人体参数尺寸的自动测量方法(HuFAMS-VP)。方法 首先,利用背景差分法,将人体从图像中分割出来;再将分割后的人体图像进行轮廓提取,从而获得人体轮廓图;然后,根据边缘检测和人体各个部位与人体身高比例等方法,获取人体几个关键部位特征点;最后,通过消失点方法(vanishing point)与比例法的结合获取人体参数尺寸。结果 根据HuFAMS-VP对7组被测人员(年龄在25±3岁,身高范围在1.7±0.2 m)进行尺寸测量,并与被测人员真实尺寸信息进行比较。由测量结果可以得到7组被测人员的绝对误差控制在±0.05 m之内,平均测量速度在2 s以内。结论 HuFAMS-VP在确保测量精度的前提下,具有操作方便、价格低廉等优势。根据测量结果,论证了本系统的准确性和鲁棒性。

关 键 词:背景差分  分割  消失点  特征识别  自动人体测量
收稿时间:2016-08-04
修稿时间:2016-10-27

Human featured automatic measurement system
Xu Huiming,Xia Likun,Yang Qi,Liu Yujie,Tang Songyuan and Yang Jian. Human featured automatic measurement system[J]. Journal of Image and Graphics, 2017, 22(2): 225-231
Authors:Xu Huiming  Xia Likun  Yang Qi  Liu Yujie  Tang Songyuan  Yang Jian
Affiliation:School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China,School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China and School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China
Abstract:Objective The common obstacles faced by all types of automatic human body measurement systems are comparably high costs and large sizes with a complex installation process. Method This study proposes a human-featured automatic measurement system based on vanishing points (HuFAMS-VP). It consists of the following parts. HuFAMS-VP initially extracts a human body image, utilizing the background subtraction method followed by image contour detection. Several critical characteristic points on the contour can then be obtained by using the edge detection technique and proportion method. Finally, we combine the methods of vanishing points with proportion measure to obtain different human body features. Result HuFAM-VP is applied to measure the human body size, and the measurements are compared with the true sizes. Results show that it can achieve accurate results at less than±5 cm between the measured and real data. Moreover, the average CPU time is less than 2 s. Conclusion The proposed system has the advantages of easy operation and low cost under the premise of high accuracy. Results show that HuFAM-VP demonstrated validity and robustness.
Keywords:background subtraction  segment  vanishing point  feature identification  automatic body measurement
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