Using 3D Statistical Shape Models for Designing Smart Clothing

Publication Type:

Conference Paper

Authors:

Scataglini, Sofia; Femke Danckaers; Haelterman, Robby; Toon Huysmans; Jan Sijbers; Andreoni, Giuseppe

Source:

Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Springer International Publishing, Cham, p.18–27 (2019)

ISBN:

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.

Research area: 
Shape Modeling