A Comparison Between Representative 3D Faces Based on Bi- and Multi-variate and Shape Based Analysis

  • Lyè GotoEmail author
  • Toon Huysmans
  • Wonsup Lee
  • Johan F. M. Molenbroek
  • Richard H. M. Goossens
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 824)


In Ergonomic product design, designers need to translate anthropometric data of the target population into product dimensions or sizing systems. Currently, sizing systems are often based on traditional anthropometric data and generally use the variation of one or two key body dimensions directly related to the product. For products that need to closely fit a certain part of the body it is relevant to incorporate multiple key dimensions. This can be realized by a multivariate approach such as a Principal Component Analysis. Over the past decades, there has been an increase in incorporating 3D imaging in anthropometric surveys. In order to integrate the use of 3D anthropometry in product sizing, representative models are used to visualize the variability of the target population. For the development of a ventilation mask for children, this study compares representative models of 3D faces based on a bivariate, multivariate and shape based analysis of 303 children’s faces.


3D anthropometry Children Ventilation mask Product sizing Design 


  1. 1.
    Dainoff M, Gordon C, Robinette K, Strauss M (2004) Guidelines for using Anthropometric data in product design - HFES 300 Commitee, Santa MonicaGoogle Scholar
  2. 2.
    Hsiao H (2013) Anthropometric procedures for protective equipment sizing and design. Hum Factors 55:6–35. Scholar
  3. 3.
    Luximon A, Zhang Y, Luximon Y, Xiao M (2012) Sizing and grading for wearable products. CAD Comput Aided Des 44:77–84. Scholar
  4. 4.
    Zhuang Z, Bradtmiller B, Shaffer RE (2007) New respirator fit test panels representing the current U.S. civilian work force. J Occup Environ Hyg 4:647–659CrossRefGoogle Scholar
  5. 5.
    Ball RM (2011) SizeChina: a 3D Anthropometric survey of the Chinese head. Delft University of TechnologyGoogle Scholar
  6. 6.
    Ballester A, Valero M, Nacher B, et al (2015) 3D body databases of the Spanish population and its application to the apparel industry. In: Proceedings of 6th International Conference 3D Body Scanning Technol Lugano, Switzerland, 27–28 October 2015, pp 232–233.
  7. 7.
    Wuhrer S, Shu C, Bose P (2012) Automatically creating design models from 3D Anthropometry data. J Comput Inf Sci Eng 12:41007. Scholar
  8. 8.
    Goto L, Lee W, Molenbroek JFM, et al (2017) Traditional and 3D scan extracted measurements of the heads and faces of Dutch children. SubmittedGoogle Scholar
  9. 9.
    Lee W, Goto L, Molenbroek JFM, Goossens RHM (2017) Analysis methods of the variation of facial size and shape based on 3D face scan images. In: Proceedings of the human factors and ergonomics society October 2017, pp 1409–1413. Scholar
  10. 10.
    Amirav I, Luder AS, Halamish A, et al (2013) Design of aerosol face masks for children using computerized 3D face analysis 26:1–7 Scholar
  11. 11.
    Goto L, Lee W, Molenbroek JFM, et al (2018) Analysis of a 3D Anthropometric Data Set of Heads and Faces of Children for Design Applications. submittedGoogle Scholar
  12. 12.
    Niu J, Li Z, Salvendy G (2009) Multi-resolution shape description and clustering of three-dimensional head data. Ergonomics 52:251–269. Scholar
  13. 13.
    Lacko D, Huysmans T, Vleugels J et al (2017) Product sizing with 3D anthropometry and k-medoids clustering. CAD Comput Aided Des 91:60–74. Scholar
  14. 14.
    Farkas LG, Posnick JC, Hreczko TM (1992) Growth patterns of the face: a morphometric study. Cleft Palate-Craniofacial J 29:308–314.;2CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of TechnologyDelftThe Netherlands
  2. 2.imec-Vision Lab, Department of PhysicsUniversity of AntwerpAntwerpBelgium
  3. 3.Handong Global UniversityPohangSouth Korea

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