|
Title
|
|
|
|
An articulating statistical shape model of the human hand
|
|
|
Author
|
|
|
|
|
|
|
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. |
|
|
|
Language
|
|
|
|
English
|
|
|
Source (book)
|
|
|
|
Advances in Human Factors in Simulation and Modeling. AHFE 2018. / Cassenti, D.N. [edit.]
|
|
|
Source (series)
|
|
|
|
Advances in Intelligent Systems and Computing; 780
|
|
|
Publication
|
|
|
|
Cham
:
Springer
,
2019
|
|
|
ISSN
|
|
|
|
2194-5357
|
|
|
ISBN
|
|
|
|
978-3-319-94222-3
978-3-319-94223-0
|
|
|
DOI
|
|
|
|
10.1007/978-3-319-94223-0_41
|
|
|
Volume/pages
|
|
|
|
p. 433-445
|
|
|
Full text (Publisher's DOI)
|
|
|
|
|
|
|
Full text (publisher's version - intranet only)
|
|
|
|
|
|