Posture normalisation of 3D body scans

Femke Danckaers, Toon Huysmans, Ann Hallemans, Guido De Bruyne, Steven Truijen, Jan Sijbers

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
77 Downloads (Pure)


For product developers that design near-body products, virtual mannequins that represent realistic body shapes, are valuable tools. With statistical shape modelling, the variability of such body shapes can be described. Shape variation captured by statistical shape models (SSMs) is often polluted by posture variations, leading to less compact models. In this paper, we propose a framework that has low computational complexity to build a posture invariant SSM, by capturing and correcting the posture of an instance. The posture-normalised SSM is shown to be substantially more compact than the non-posture-normalised SSM. Practitioner summary: Statistical shape modelling is a technique to map out the variability of (body) shapes. This variability is often polluted by variations in posture. In this paper, we propose a framework to build a posture invariant statistical shape model. Abbreviations: SSM: statistical shape model; 1D: one-dimensional; 3D: three-dimensional; DHM: digital human model; LBS: linear blend skinning; PCA: princial component analysis; PC: principal component; TTR: thumb tip reach.

Original languageEnglish
Pages (from-to)834-848
Number of pages15
JournalErgonomics: an international journal of research and practice in human factors and ergonomics
Issue number6
Publication statusPublished - 2019

Bibliographical note

Accepted author manuscript


  • 3D body scan
  • Posture modelling
  • posture normalisation
  • statistical shape model


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