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Proceedings Article, Paper
@InProceedings
Beitrag in Tagungsband, Workshop

Author, Editor
Author(s):
Theobalt, Christian
de Aguiar, Edilson
Magnor, Marcus
Theisel, Holger
Seidel, Hans-Peter		dblp
dblp
dblp
dblp
dblp
Editor(s):
Lau, Rynson
Baciu, George		dblp
dblp
Not MPII Editor(s):
Lau, Rynson
Baciu, George
BibTeX cite key*:
TheobaltVRST2004
Title, Booktitle
Title*:
Marker-free Kinematic Skeleton Estimation from Sequences of Volume Data
Booktitle*:
ACM Symposium on Virtual Reality Software and Technology (VRST 2004)
Event, URLs
Conference URL::
http://www.cs.cityu.edu.hk/~vrst2004/
Downloading URL:
Event Address*:
Hong Kong, China
Language:
English
Event Date*
(no longer used):
Organization:
Association of Computing Machinery (ACM)
Event Start Date:
10 November 2004
Event End Date:
12 November 2004
Publisher
Name*:
ACM
URL:
http://www.acm.org
Address*:
New York, USA
Type:
Vol, No, Year, pp.
Series:
Volume:
Number:
Month:
November
Pages:
57-64
Year*:
2004
VG Wort Pages:
40
ISBN/ISSN:
1-58113-907-1
Sequence Number:
DOI:
Note, Abstract, ©
(LaTeX) Abstract:
\begin{abstract}
For realistic animation of an artificial character a body model that represents
the character's kinematic structure is required.
%
Hierarchical skeleton models
are widely used which represent bodies as chains of bones with interconnecting joints.
%
In video motion capture, animation parameters are derived from the performance
of a subject in the real world.
%
For this acquisition procedure too, a kinematic body model
is required.
%
Typically, the generation of such a model for tracking and animation
is, at best, a semi-automatic process. We present a novel approach that estimates
a hierarchical skeleton model of an arbitrary moving subject from sequences of voxel data
that were reconstructed from multi-view video footage.
Our method does not require a-priori information about the body structure.
%The approach is particularly
%suited as a component of a marker-free optical motion capture system.
We demonstrate its performance using synthetic and real data.
\end{abstract}
Keywords:
Motion Capture, Virtual Reality, Voxel Volumes, Model Estimation, Kinematic Skeleton
Download
Access Level:
Public

Correlation
MPG Unit:
Max-Planck-Institut für Informatik
MPG Subunit:
Computer Graphics Group
Appearance:
MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{TheobaltVRST2004,
AUTHOR = {Theobalt, Christian and de Aguiar, Edilson and Magnor, Marcus and Theisel, Holger and Seidel, Hans-Peter},
 EDITOR = {Lau, Rynson and Baciu, George},
 TITLE = {Marker-free Kinematic Skeleton Estimation from Sequences of Volume Data},
 BOOKTITLE = {ACM Symposium on Virtual Reality Software and Technology (VRST 2004)},
 PUBLISHER = {ACM},
 YEAR = {2004},
 ORGANIZATION = {Association of Computing Machinery (ACM)},
 PAGES = {57--64},
 ADDRESS = {Hong Kong, China},
 MONTH = {November},
 ISBN = {1-58113-907-1},
}

Entry last modified by Anja Becker, 02/04/2005
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Editor(s)
Christian Theobalt		Created
12/28/2004 04:31:43 PM
Revisions
2.
1.
0.

Editor(s)
Anja Becker
Christian Theobalt
Christian Theobalt

Edit Dates
04.02.2005 11:49:20
12/28/2004 04:33:10 PM
12/28/2004 04:31:43 PM