Moving Statistical Body Shape Models Using Blender

Conference Paper (2019)
Author(s)

Sofia Scataglini (Royal Military Academy, Military Hospital Queen Astrid)

Femke Danckaers (Universiteit Antwerpen)

Robby Haelterman (Royal Military Academy)

T. Huysmans (TU Delft - Human Factors)

Jan Sijbers (Universiteit Antwerpen)

Research Group
Human Factors
DOI related publication
https://doi.org/10.1007/978-3-319-96077-7_4
More Info
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Publication Year
2019
Language
English
Research Group
Human Factors
Volume number
V
Pages (from-to)
28-38
ISBN (print)
978-3-319-96076-0
ISBN (electronic)
978-3-319-96077-7

Abstract

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.

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