Automated positioning of breast feature points for parameter extraction based on 3D point cloud

IF 3 2区 工程技术 Q2 ENGINEERING, INDUSTRIAL
Zejun Zhong , Beibei Zhang , Bingfei Gu , Yue Sun
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引用次数: 0

Abstract

To achieve automatic extraction of parameter for female breast shape analysis, this paper proposed a “point-parameter-type” method based on 3D point cloud data. To standardize the measurement method, nine feature points (i.e., BBP, BP, FAP, FNP, LUBP, LBP, MBP, RUBP and UBP) and three lines (i.e., BBL, BL and BC) were firstly defined according to the characteristics of breast shape. Utilizing the 3D point cloud data, four positioning methods, including Max-Distance, Inflection-Points, Slope and Intersection-Point, were proposed to automate the positioning of feature points. Finally, breast morphological parameters for shape classification were calculated or predicted using computational models, and 140 subjects were randomly selected to verify the method accuracy. The results indicated that the recognition accuracy rates were 94.74 % for type FC, 89.06 % for type UO, and 89.47 % for type PO, demonstrating that this method is feasible. This study aims to establish a foundation for the automatic measurement of breast and provide valuable support for bra size recommendation for consumers during online shopping.
基于三维点云的乳房特征点自动定位参数提取
为了实现女性乳房形状分析参数的自动提取,本文提出了一种基于三维点云数据的“点参数型”方法。为了使测量方法标准化,首先根据乳房形状特征定义了9个特征点(BBP、BP、FAP、FNP、LUBP、LBP、MBP、RUBP、UBP)和3条线(BBL、BL、BC)。利用三维点云数据,提出了最大距离定位、拐点定位、斜率定位和交点定位四种定位方法,实现了特征点的自动定位。最后,利用计算模型计算或预测用于形状分类的乳腺形态学参数,并随机选取140名受试者验证方法的准确性。结果表明,FC型、UO型和PO型的识别准确率分别为94.74%、89.06%和89.47%,表明该方法是可行的。本研究旨在为乳房自动测量奠定基础,并为消费者在网上购物时推荐胸罩尺寸提供有价值的支持。
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来源期刊
International Journal of Industrial Ergonomics
International Journal of Industrial Ergonomics 工程技术-工程:工业
CiteScore
6.40
自引率
12.90%
发文量
110
审稿时长
56 days
期刊介绍: The journal publishes original contributions that add to our understanding of the role of humans in today systems and the interactions thereof with various system components. The journal typically covers the following areas: industrial and occupational ergonomics, design of systems, tools and equipment, human performance measurement and modeling, human productivity, humans in technologically complex systems, and safety. The focus of the articles includes basic theoretical advances, applications, case studies, new methodologies and procedures; and empirical studies.
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