Using 3D Statistical Shape Models for Designing Smart Clothing

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

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

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
EditorsSebastiano Bagnara, Riccardo Tartaglia, Sara Albolino, Thomas Alexander, Yushi Fujita
Place of PublicationCham
PublisherSpringer
Pages18-27
Number of pages10
VolumeV
ISBN (Electronic)978-3-319-96077-7
ISBN (Print)978-3-319-96076-0
DOIs
Publication statusPublished - 2019
Event IEA 2018: 20th Congress of the International Ergonomics Association - Florence, Italy
Duration: 26 Aug 201830 Aug 2018
Conference number: 20

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume822
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference IEA 2018: 20th Congress of the International Ergonomics Association
Abbreviated title IEA 2018
CountryItaly
CityFlorence
Period26/08/1830/08/18

Keywords

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

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