• Thomas Peeters
  • Jochen Vleugels
  • Stijn Verwulgen
  • Femke Danckaers
  • Toon Huysmans
  • Jan Sijbers
  • Guido De Bruyne

In times of online shopping, it is a challenge to select the right size of the desired clothing without fitting it before ordering. Therefore, this study describes three techniques to predict 3D upper body dimensions. The first method used basic personal parameters (gender, age, weight and length), the second technique used also the shoulder width and the last method used a 3D Styku scan to add extra input parameters. The accuracy of the three prediction methods was compared against hand measurements for 17 upper body dimensions of 37 subjects. The Intraclass Correlation Coefficient increases with 11.2% for the Styku method compared to the other methods. For chest, hip and waist measurements, the basic method is reliable to predict 3D body dimensions and indicate the right size from an existing collection. For more accurate upper body dimensions as needed for producing custom made clothing, a 3D Styku scan can supply the desired input.

Original languageEnglish
Title of host publicationAdvances in Additive Manufacturing, Modeling Systems and 3D Prototyping - Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping
EditorsEmilio Rossi, Massimo Di Nicolantonio, Thomas Alexander
Place of PublicationCham
Number of pages7
ISBN (Electronic)978-3-030-20216-3
ISBN (Print)978-3-030-20215-6
Publication statusPublished - 2020
EventAHFE 2019: International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping - Washington D.C., United States
Duration: 24 Jul 201928 Jul 2019

Publication series

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


ConferenceAHFE 2019
CountryUnited States
CityWashington D.C.

    Research areas

  • Body dimension prediction, Custom made clothing, Shape modelling

ID: 52659223