Using 3D statistical shape models for designing smart clothing

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V
Subtitle of host publicationHuman Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control
EditorsYushi Fujita, Sebastiano Bagnara, Riccardo Tartaglia, Sara Albolino, Thomas Alexander
PublisherSpringer
Pages18-27
Number of pages10
ISBN (Print)9783319960760
DOIs
Publication statusPublished - 2019
Event20th Congress of the International Ergonomics Association, IEA 2018 - Florence, Italy
Duration: 26 Aug 201830 Aug 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume822
ISSN (Print)2194-5357

Conference

Conference20th Congress of the International Ergonomics Association, IEA 2018
Country/TerritoryItaly
CityFlorence
Period26/08/1830/08/18

Keywords

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

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