Skip to main content

3D Body Modelling and Applications

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 826)

Abstract

Human body metrics have become a significant source of product innovation to industries where consumer fit, comfort and ergonomic considerations are key factors. This is especially the case for fashion (e.g. footwear or apparel), health (e.g. orthotics or prosthetics), transport and aerospace (e.g. seats or human-machine interfaces), and safety (e.g. protective equipment or workstations) among others. Large-scale databases of 3D body scans are today a research tool for most of the leading companies of those sectors.

In the last few years, new emerging businesses using 3D body data (e.g. garment and footwear customization, size recommendation, health monitoring) are increasing the number and size of 3D body scan repositories. 3D body databases are growing very fast and the development of 3D modelling tools is leveraging the practical application and exploitation of these data.

This paper presents three applications of 3D body modelling methods based on Principal Component Analysis (PCA): (1) shape analysis applied to the ergonomic sizing and design of products, (2) creation of 3D avatars from body measurements, and (3) serial 3D creation of harmonised watertight meshes acquired with any type of 3D body scanner.

Keywords

  • 3D human models
  • Body avatars
  • 3D mannequins
  • Anthropometry

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-96065-4_66
  • Chapter length: 14 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   229.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-96065-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   299.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.

References

  1. Pheasant S (1991) Ergonomics, work and health. Palgrave, Basingstoke

    CrossRef  Google Scholar 

  2. Duffy VG (2016) Handbook of digital human modeling: research for applied ergonomics and human factors engineering. CRC Press, Boca Raton

    Google Scholar 

  3. Reed MP et al (2014) Developing and implementing parametric human body shape models in ergonomics software. In: Proceedings of the 3rd international digital human modeling conference, Tokyo

    Google Scholar 

  4. Robinette, KM, Daanen H, Paquet E (1999) The CAESAR project: a 3-D surface anthropometry survey. In: Proceedings of the second international conference on 3-D digital imaging and modeling, IEEE (1999)

    Google Scholar 

  5. Ballester A et al (2015) 3D body databases of the spanish population and its application to the apparel industry. In: Proceedings of 6th international conference on 3D body scanning technologies, Lugano, Switzerland

    Google Scholar 

  6. Trieb R et al (2013) EUROFIT—integration, homogenisation and extension of the scope of large 3D anthropometric data pools for product development. In: 4th International conference and exhibition on 3D body scanning technologies, Long Beach, CA, USA (2013)

    Google Scholar 

  7. Allen B, Curless B, Popović Z (2003) The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans Graphics (TOG) 22(3):587–594

    CrossRef  Google Scholar 

  8. Reed MP, Park BKD (2017) Comparison of boundary manikin generation methods. In: 5th International digital human modeling symposium

    Google Scholar 

  9. Zeng Y, Fu J, Chao H (2017) 3D human body reshaping with anthropometric modeling. In: International conference on internet multimedia computing and service. Springer, Singapore

    Google Scholar 

  10. Reed MP et al (2014) Developing and implementing parametric human body shape models in ergonomics software. In: Proceedings of the 3rd international digital human modeling conference, Tokyo

    Google Scholar 

  11. Wuhrer S, Shu C (2013) Estimating 3D human shapes from measurements. Mach Vis Appl 24(6):1133–1147

    CrossRef  Google Scholar 

  12. Koo B-Y et al (2015) Example-based statistical framework for parametric modeling of human body shapes. Comput Ind 73:23–38

    CrossRef  Google Scholar 

  13. Baek S-Y, Lee K (2012) Parametric human body shape modeling framework for human-centered product design. Comput Aided Des 44(1):56–67

    CrossRef  Google Scholar 

  14. Seo H, Yeo YI, Wohn K (2006) 3D body reconstruction from photos based on range scan. In: International conference on technologies for e-learning and digital entertainment. Springer, Heidelberg (2006)

    Google Scholar 

  15. Xi P, Lee W-S, Shu C (2007) A data-driven approach to human-body cloning using a segmented body database. In: 15th pacific conference on computer graphics and applications. PG 2007. IEEE

    Google Scholar 

  16. Zhu S, Mok PY, Kwok YL (2013) An efficient human model customization method based on orthogonal-view monocular photos. Comput Aided Des 45(11):1314–1332

    CrossRef  Google Scholar 

  17. Saito S et al (2014) Model-based 3D human shape estimation from silhouettes for virtual fitting. In: Three-dimensional image processing, measurement (3DIPM), and applications 2014, vol 9013. International Society for Optics and Photonics

    Google Scholar 

  18. Mok PY, Zhu S (2018) Precise shape estimation of dressed subjects from two-view image sets. In: Applications of computer vision in fashion and textiles, pp 273–292

    Google Scholar 

  19. Ballester A et al (2016) Data-driven three-dimensional reconstruction of human bodies using a mobile phone app. Int J Digital Hum 1(4):361–388

    CrossRef  Google Scholar 

  20. Weiss, A, Hirshberg D, Black MJ (2011) Home 3D body scans from noisy image and range data. In: 2011 IEEE international conference on computer vision (ICCV). IEEE

    Google Scholar 

  21. Lu Y et al. Accurate nonrigid 3D human body surface reconstruction using commodity depth sensors. Comput Animation Virt Worlds e1807

    Google Scholar 

  22. Park B-K, Reed MP (2014) Rapid generation of custom avatars using depth cameras. In: Proceedings of the 3rd international digital human modeling conference

    Google Scholar 

  23. Tong J et al (2012) Scanning 3D full human bodies using kinects. IEEE Trans Vis Comput Graphics 18(4):643–650

    CrossRef  Google Scholar 

  24. Allen B et al (2006) Learning a correlated model of identity and pose-dependent body shape variation for real-time synthesis. In: Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on computer animation. Eurographics Association

    Google Scholar 

  25. Anguelov D et al (2005) SCAPE: shape completion and animation of people. In: ACM transactions on graphics (TOG), vol 24, no 3. ACM (2005)

    Google Scholar 

  26. Hasler N et al (2009) A statistical model of human pose and body shape. In: Computer graphics forum, vol 28, no 2. Blackwell Publishing Ltd

    Google Scholar 

  27. Hirshberg DA et al (2012) Coregistration: simultaneous alignment and modeling of articulated 3D shape. In: European conference on computer vision. Springer, Heidelberg

    Google Scholar 

  28. Istook CL, Hwang S-J (2001) 3D body scanning systems with application to the apparel industry. J Fashion Mark Manag Int J 5(2):120–132

    CrossRef  Google Scholar 

  29. D’Apuzzo N, Gruen A (2009) Recent advances in 3D full body scanning with applications to fashion and apparel. Optical 3-D measurement techniques IX (2009)

    Google Scholar 

  30. Treleaven P, Wells J (2007) 3D body scanning and healthcare applications. Computer 40(7):28–34

    CrossRef  Google Scholar 

  31. Alemany S, González JC, Nácher B, Soriano C, Arnáiz C, Heras H (2010) Anthropometric survey of the Spanish female population aimed at the apparel industry. In: Proceedings of the 2010 international conference on 3D body scanning technologies. Lugano, Switzerland

    Google Scholar 

  32. Amberg B, Romdhani S, Vetter T (2007 June) Optimal step nonrigid ICP algorithms for surface registration. In: IEEE conference on computer vision and pattern recognition, 2007. CVPR 2007. IEEE, pp 1–8

    Google Scholar 

  33. Sumner RW, Popović J (2004, August). Deformation transfer for triangle meshes. In: ACM Transactions on graphics (TOG), vol 23, no 3, pp 399–405. ACM

    Google Scholar 

  34. Gower JC (1975) Generalized procrustes analysis. Psychometrika 40(1):33–51

    MathSciNet  CrossRef  Google Scholar 

  35. Zehner GF, Meindl RS, Hudson JA (1993) A multivariate anthropometric method for crew station design. Kent State University oH

    Google Scholar 

  36. Robinette KM, McConville JT (1981) An alternative to percentile models (No 810217). SAE technical paper

    Google Scholar 

  37. Robinette KM (1998) Multivariate methods in engineering anthropometry. In: Proceedings of the human factors and ergonomics society annual meeting vol 42, no 10. SAGE Publications, Sage, Los Angeles

    Google Scholar 

  38. Lacko D et al (2017) Product sizing with 3D anthropometry and k-medoids clustering. Comput Aided Des 91:60–74

    CrossRef  Google Scholar 

  39. Lee W et al (2016) Application of massive 3D head and facial scan datasets in ergonomic head-product design. Int J Digital Hum 1(4):344–360

    CrossRef  Google Scholar 

  40. Veitch D, Veitch L, Henneberg M (2007) Sizing for the clothing industry using principal component analysis—an Australian example. J ASTM Int 4(3):1–12

    Google Scholar 

  41. Durá JV, Caprara G, Ballester A, Pierola A, Kozomara Z (2018) Preliminary results of the InKreate Project. Revista de Biomecánica 65

    Google Scholar 

  42. Han H, Nam Y, Choi K (2010) Comparative analysis of 3D body scan measurements and manual measurements of size Korea adult females. Int J Ind Ergon 40(5):530–540

    CrossRef  Google Scholar 

  43. Markiewicz Ł et al (2017) 3D anthropometric algorithms for the estimation of measurements required for specialized garment design. Expert Syst Appl 85:366–385

    CrossRef  Google Scholar 

Download references

Acknowledgments

The authors thank the European Commission, the Instituto Valenciano de Competitividad Empresarial (IVACE) and the Agencia Estatal de Investigación del Ministerio de Economía, Industria y Competiti-vidad (MINECO) for the financial support of this research though the following projects: In-Kreate (funded by the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement no. 731885), BodyPass (funded by the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement no. 779780), 3DBODY_HUB (submitted to IVACE with a funding of Generalitat Valenciana and the European Regional Development Fund and the proposal nº IMDEEA/2018/49) and Torres Quevedo (funded by MINECO under the program Torres Quevedo 2016).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Alemany .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Alemany, S. et al. (2019). 3D Body Modelling and Applications. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 826. Springer, Cham. https://doi.org/10.1007/978-3-319-96065-4_66

Download citation