Moving Statistical Body Shape Models Using Blender

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

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

737 Citations (Scopus)


In this paper, we present a new framework to integrate movement acquired by a motion capture system to a statistical body shape model using Blender. This provides a visualization of a digital human model based upon anthropometry and biomechanics of the subject. A moving statistical body shape model helps to visualize physical tasks with inter-individual variability in body shapes as well as anthropometric dimensions. This parametric modeling approach is useful for reliable prediction and simulation of the body shape movement of a specific population with a few given predictors such as stature, body mass index and age.
Original languageEnglish
Title of host publicationProceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)
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
Number of pages11
ISBN (Electronic)978-3-319-96077-7
ISBN (Print)978-3-319-96076-0
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
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference IEA 2018: 20th Congress of the International Ergonomics Association
Abbreviated title IEA 2018


  • Blender
  • Digital human modeling
  • Motion capture
  • Statistical body shape modeling


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