Using 3D Statistical Shape Models for Designing Smart Clothing

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Using 3D Statistical Shape Models for Designing Smart Clothing

Conference Paper (2019)

Author(s)

Sofia Scataglini (Royal Military Academy, Military Hospital Queen Astrid)

Femke Danckaers (Universiteit Antwerpen)

Robby Haelterman (Royal Military Academy)

Toon Huysmans (Universiteit Antwerpen, TU Delft - Human Factors)

Jan Sijbers (Universiteit Antwerpen)

Giuseppe Andreoni (Politecnico di Milano)

Research Group

Human Factors

DOI related publication

https://doi.org/10.1007/978-3-319-96077-7_3

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

To reference this document use:

https://resolver.tudelft.nl/uuid:acf7d5ae-dd0d-4cdd-b8f2-97fde7dfd9a0

More Info

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Publication Year

2019

Language

English

Research Group

Human Factors

Volume number

V

Pages (from-to)

18-27

Publisher

Springer

ISBN (print)

978-3-319-96076-0

ISBN (electronic)

978-3-319-96077-7

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.

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