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Using 3D Statistical Shape Models for Designing Smart Clothing

  • Sofia ScatagliniEmail author
  • Femke Danckaers
  • Robby Haelterman
  • Toon Huysmans
  • Jan Sijbers
  • Giuseppe Andreoni
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 822)

Abstract

In this paper we present an innovative approach to design smart clothing using statistical body shape modeling (SBSM) from the CAESAR™ dataset. A combination of different digital technologies and applications are used to create a common co-design workflow for garment design. User and apparel product design and developers can get personalized prediction of cloth sizing, fitting and aesthetics.

Keywords

Statistical body shape modeling (SBSM) Anthropometry Blender Motion capture Smart clothing 

Notes

Acknowledgements

This work was supported by the Agency for Innovation by Science and Technology in Flanders (IWT-SB 141520). We acknowledge Alain Vanhove of the Royal Military Academy for his contribution in the 3D modeling. We would also like to thank all the participants in this study.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sofia Scataglini
    • 1
    • 2
    Email author
  • Femke Danckaers
    • 3
  • Robby Haelterman
    • 1
  • Toon Huysmans
    • 3
    • 4
  • Jan Sijbers
    • 3
  • Giuseppe Andreoni
    • 5
  1. 1.Department of Mathematics (MWMW)Royal Military AcademyBrusselsBelgium
  2. 2.Military Hospital Queen AstridBrusselsBelgium
  3. 3.imec – Vision Lab, Department of PhysicsUniversity of AntwerpAntwerpBelgium
  4. 4.Applied Ergonomics and Design, Department of Industrial DesignTU DelftDelftNetherlands
  5. 5.Department of DesignPolitecnico di MilanoMilanItaly

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