|
Title
|
|
|
|
Automatic generation of statistical shape models in motion
|
|
|
Author
|
|
|
|
|
|
|
Abstract
|
|
|
|
| Statistical body shape modeling (SBSM) is a well-known technique to map out the variability of body shapes and is commonly used in 3D anthropometric analyses. In this paper, a new approach to integrate movement acquired by a motion capture system with a body shape is proposed. This was done by selecting landmarks on a body shape model, and predicting a body shape based on features. Then, a virtual skeleton was generated relative to those landmarks. This skeleton was parented to a body shape, allowing to modify its pose and to add pre-recorded motion to different body shapes in a realistic way. |
|
|
|
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_16
|
|
|
Volume/pages
|
|
|
|
p. 170-178
|
|
|
Full text (Publisher's DOI)
|
|
|
|
|
|