An Articulating Statistical Shape Model of the Human Hand

Jeroen Van Houtte; Kristina  Stanković; Brian G. Booth; Femke  Danckaers; Véronique  Bertrand; Frederik Verstreken; Jan Sijbers; Toon Huysmans

doi:10.1007/978-3-319-94223-0_41

An Articulating Statistical Shape Model of the Human Hand

Jeroen Van Houtte, Kristina Stanković, Brian G. Booth, Femke Danckaers, Véronique Bertrand, Frederik Verstreken, Jan Sijbers, Toon Huysmans

Human Factors

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

8 Citations (SciVal)

Abstract

This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.

Original language	English
Title of host publication	Advances in Human Factors in Simulation and Modeling
Subtitle of host publication	Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization
Editors	Daniel N. Cassenti
Place of Publication	Cham
Publisher	Springer
Pages	433-445
Number of pages	13
ISBN (Electronic)	978-3-319-94223-0
ISBN (Print)	978-3-319-94222-3
DOIs	https://doi.org/10.1007/978-3-319-94223-0_41
Publication status	Published - 2019
Event	AHFE 2018 : International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization - Orlando, United States Duration: 21 Jul 2018 → 25 Jul 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	780
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	AHFE 2018
Country/Territory	United States
City	Orlando
Period	21/07/18 → 25/07/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Articulation-model
Registration
Human hand
Statistical shape modelling

Access to Document

10.1007/978-3-319-94223-0_41

Cite this

Van Houtte, J., Stanković, K., Booth, B. G., Danckaers, F., Bertrand, V., Verstreken, F., Sijbers, J., & Huysmans, T. (2019). An Articulating Statistical Shape Model of the Human Hand. In D. N. Cassenti (Ed.), Advances in Human Factors in Simulation and Modeling: Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization (pp. 433-445). (Advances in Intelligent Systems and Computing ; Vol. 780). Springer. https://doi.org/10.1007/978-3-319-94223-0_41

Van Houtte, Jeroen ; Stanković, Kristina ; Booth, Brian G. et al. / An Articulating Statistical Shape Model of the Human Hand. Advances in Human Factors in Simulation and Modeling: Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization. editor / Daniel N. Cassenti. Cham : Springer, 2019. pp. 433-445 (Advances in Intelligent Systems and Computing ).

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title = "An Articulating Statistical Shape Model of the Human Hand",

abstract = "This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.",

keywords = "Articulation-model, Registration, Human hand , Statistical shape modelling",

author = "{Van Houtte}, Jeroen and Kristina Stankovi{\'c} and Booth, {Brian G.} and Femke Danckaers and V{\'e}ronique Bertrand and Frederik Verstreken and Jan Sijbers and Toon Huysmans",

year = "2019",

doi = "10.1007/978-3-319-94223-0_41",

language = "English",

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editor = "Cassenti, {Daniel N.}",

booktitle = "Advances in Human Factors in Simulation and Modeling",

note = "AHFE 2018 : International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization ; Conference date: 21-07-2018 Through 25-07-2018",

}

Van Houtte, J, Stanković, K, Booth, BG, Danckaers, F, Bertrand, V, Verstreken, F, Sijbers, J & Huysmans, T 2019, An Articulating Statistical Shape Model of the Human Hand. in DN Cassenti (ed.), Advances in Human Factors in Simulation and Modeling: Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization. Advances in Intelligent Systems and Computing , vol. 780, Springer, Cham, pp. 433-445, AHFE 2018 , Orlando, Florida, United States, 21/07/18. https://doi.org/10.1007/978-3-319-94223-0_41

An Articulating Statistical Shape Model of the Human Hand. / Van Houtte, Jeroen; Stanković, Kristina ; Booth, Brian G. et al.
Advances in Human Factors in Simulation and Modeling: Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization. ed. / Daniel N. Cassenti. Cham: Springer, 2019. p. 433-445 (Advances in Intelligent Systems and Computing ; Vol. 780).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - An Articulating Statistical Shape Model of the Human Hand

AU - Van Houtte, Jeroen

AU - Stanković, Kristina

AU - Booth, Brian G.

AU - Danckaers, Femke

AU - Bertrand, Véronique

AU - Verstreken, Frederik

AU - Sijbers, Jan

AU - Huysmans, Toon

PY - 2019

Y1 - 2019

N2 - This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.

AB - This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.

KW - Articulation-model

KW - Registration

KW - Human hand

KW - Statistical shape modelling

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DO - 10.1007/978-3-319-94223-0_41

M3 - Conference contribution

SN - 978-3-319-94222-3

T3 - Advances in Intelligent Systems and Computing

SP - 433

EP - 445

BT - Advances in Human Factors in Simulation and Modeling

A2 - Cassenti, Daniel N.

PB - Springer

CY - Cham

T2 - AHFE 2018

Y2 - 21 July 2018 through 25 July 2018

ER -

Van Houtte J, Stanković K, Booth BG, Danckaers F, Bertrand V, Verstreken F et al. An Articulating Statistical Shape Model of the Human Hand. In Cassenti DN, editor, Advances in Human Factors in Simulation and Modeling: Proceedings of the AHFE 2018 International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization. Cham: Springer. 2019. p. 433-445. (Advances in Intelligent Systems and Computing ). doi: 10.1007/978-3-319-94223-0_41

An Articulating Statistical Shape Model of the Human Hand

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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