Moving statistical body shape models using blender

Sofia Scataglini; Femke Danckaers; Rob Haelterman; Toon Huysmans; Jan Sijbers

doi:10.1007/978-3-319-96077-7_4

Moving statistical body shape models using blender

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

Universiteit Antwerpen
Delft University of Technology

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › peer review

433 Citaten (Scopus)

Samenvatting

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.

Originele taal-2	Engels
Titel	Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V
Subtitel	Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control
Redacteuren	Yushi Fujita, Sebastiano Bagnara, Riccardo Tartaglia, Sara Albolino, Thomas Alexander
Uitgeverij	Springer
Pagina's	28-38
Aantal pagina's	11
ISBN van geprinte versie	9783319960760
DOI's	https://doi.org/10.1007/978-3-319-96077-7_4
Status	Gepubliceerd - 2019
Evenement	20th Congress of the International Ergonomics Association, IEA 2018 - Florence, Italië Duur: 26 aug. 2018 → 30 aug. 2018

Publicatie series

Naam	Advances in Intelligent Systems and Computing
Volume	822
ISSN van geprinte versie	2194-5357

Congres

Congres	20th Congress of the International Ergonomics Association, IEA 2018
Land/Regio	Italië
Stad	Florence
Periode	26/08/18 → 30/08/18

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10.1007/978-3-319-96077-7_4

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Citeer dit

Scataglini, S., Danckaers, F., Haelterman, R., Huysmans, T., & Sijbers, J. (2019). Moving statistical body shape models using blender. In Y. Fujita, S. Bagnara, R. Tartaglia, S. Albolino, & T. Alexander (editors), Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V: Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control (blz. 28-38). (Advances in Intelligent Systems and Computing; Vol. 822). Springer. https://doi.org/10.1007/978-3-319-96077-7_4

Scataglini, Sofia ; Danckaers, Femke ; Haelterman, Rob et al. / Moving statistical body shape models using blender. Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V: Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control. redacteur / Yushi Fujita ; Sebastiano Bagnara ; Riccardo Tartaglia ; Sara Albolino ; Thomas Alexander. Springer, 2019. blz. 28-38 (Advances in Intelligent Systems and Computing).

@inproceedings{e8edb7cc908b45598d6b74ae10fccef7,

title = "Moving statistical body shape models using blender",

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.",

keywords = "Blender, Digital human modeling, Motion capture, Statistical body shape modeling",

author = "Sofia Scataglini and Femke Danckaers and Rob Haelterman and Toon Huysmans and Jan Sijbers",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 20th Congress of the International Ergonomics Association, IEA 2018 ; Conference date: 26-08-2018 Through 30-08-2018",

year = "2019",

doi = "10.1007/978-3-319-96077-7\_4",

language = "English",

isbn = "9783319960760",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "28--38",

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Scataglini, S, Danckaers, F, Haelterman, R, Huysmans, T & Sijbers, J 2019, Moving statistical body shape models using blender. in Y Fujita, S Bagnara, R Tartaglia, S Albolino & T Alexander (reds.), Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V: Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control. Advances in Intelligent Systems and Computing, vol. 822, Springer, blz. 28-38, 20th Congress of the International Ergonomics Association, IEA 2018, Florence, Italië, 26/08/18. https://doi.org/10.1007/978-3-319-96077-7_4

Moving statistical body shape models using blender. / Scataglini, Sofia; Danckaers, Femke; Haelterman, Rob et al.
Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V: Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control. reds. / Yushi Fujita; Sebastiano Bagnara; Riccardo Tartaglia; Sara Albolino; Thomas Alexander. Springer, 2019. blz. 28-38 (Advances in Intelligent Systems and Computing; Vol. 822).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › peer review

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AU - Scataglini, Sofia

AU - Danckaers, Femke

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AU - Sijbers, Jan

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

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AB - 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.

KW - Blender

KW - Digital human modeling

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Scataglini S, Danckaers F, Haelterman R, Huysmans T, Sijbers J. Moving statistical body shape models using blender. In Fujita Y, Bagnara S, Tartaglia R, Albolino S, Alexander T, redacteurs, Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume V: Human Simulation and Virtual Environments, Work With Computing Systems WWCS, Process Control. Springer. 2019. blz. 28-38. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-96077-7_4

Moving statistical body shape models using blender

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