Journal Article
@Article
Artikel in Fachzeitschrift


Show entries of:

this year (2019) | last year (2018) | two years ago (2017) | Notes URL

Action:

login to update

Options:




Library Locked Library locked




Author, Editor(s)

Author(s):

Neumann, Thomas
Varanasi, Kiran
Hasler, Nils
Wacker, Marcus
Magnor, Markus
Theobalt, Christian

dblp
dblp
dblp
dblp
dblp
dblp

Not MPG Author(s):

Neumann, Thomas
Wacker, Marcus
Magnor, Markus

BibTeX cite key*:

Neumann2013

Title

Title*:

Capture and Statistical Modeling of Arm-Muscle Deformations

Journal

Journal Title*:

Computer Graphics Forum (Proceedings EUROGRAPHICS 2013)

Journal's URL:


Download URL
for the article:


Language:

English

Publisher

Publisher's
Name:

Eurographics Association

Publisher's URL:


Publisher's
Address:

Geneve, Switzerland

ISSN:


Vol, No, pp, Date

Volume*:

32

Number:

?

Publishing Date:

May 2013

Pages*:

?-?

Number of
VG Pages:


Page Start:


Page End:


Sequence Number:


DOI:


Note, Abstract, ©

Note:


(LaTeX) Abstract:

We present a comprehensive data-driven statistical model for skin and muscle deformation of the human shoulder-arm complex.
Skin deformations arise from complex bio-physical effects such as
non-linear elasticity of muscles, fat, and connective tissue;
and vary with physiological constitution of the subjects and external forces applied during motion.
Thus, they are hard to model by direct physical simulation.
Our alternative approach is based on learning deformations
from multiple subjects performing different exercises under varying external forces.
We capture the training data through a novel multi-camera approach that is able to reconstruct fine-scale muscle detail in motion.
The resulting reconstructions from several people are aligned into one common shape parametrization,
and learned using a semi-parametric non-linear method.
Our learned data-driven model is fast, compact and controllable with a small set of intuitive parameters - pose, body shape and external forces,
through which a novice artist can interactively produce complex muscle deformations.
Our method is able to capture and synthesize fine-scale muscle bulge effects to a greater level of realism than achieved previously. We provide quantitative and qualitative validation of our method.

URL for the Abstract:


Categories,
Keywords:


HyperLinks / References / URLs:


Copyright Message:


Personal Comments:


Download
Access Level:

Internal

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Audience:

popular

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{Neumann2013,
AUTHOR = {Neumann, Thomas and Varanasi, Kiran and Hasler, Nils and Wacker, Marcus and Magnor, Markus and Theobalt, Christian},
TITLE = {Capture and Statistical Modeling of Arm-Muscle Deformations},
BOOKTITLE = {Proceedings of the 34th Annual Conference of the European Association for Computer Graphics},
JOURNAL = {Computer Graphics Forum (Proceedings EUROGRAPHICS 2013)},
PUBLISHER = {Eurographics Association},
YEAR = {2013},
NUMBER = {?},
VOLUME = {32},
PAGES = {?--?},
SERIES = {Computer Graphics Forum},
ADDRESS = {Girona (Spain)},
MONTH = {May},
}


Entry last modified by Oliver Klehm, 01/30/2014
Show details for Edit History (please click the blue arrow to see the details)Edit History (please click the blue arrow to see the details)
Hide details for Edit History (please click the blue arrow to see the details)Edit History (please click the blue arrow to see the details)

Editor(s)
[Library]
Created
02/06/2013 05:44:45 PM
Revisions
7.
6.
5.
4.
3.
Editor(s)
Oliver Klehm
Oliver Klehm
Uwe Brahm
Uwe Brahm
Uwe Brahm
Edit Dates
02/12/2013 06:53:33 PM
02/12/2013 05:19:56 PM
02/12/2013 05:13:05 PM
02/12/2013 05:12:56 PM
02/12/2013 05:12:45 PM