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Author, Editor

Author(s):

de Aguiar, Edilson
Stoll, Carsten
Ahmed, Naveed
Seidel, Hans-Peter

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Not MPG Author(s):

Theobalt, Christian
Thrun, Sebastian

Editor(s):

Turk, Greg

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Not MPII Editor(s):

Turk, Greg

BibTeX cite key*:

deAguiar2008

Title, Booktitle

Title*:

Performance Capture from Sparse Multi-View Video

Booktitle*:

Proceedings of ACM SIGGRAPH 2008

Event, URLs

URL of the conference:

http://www.siggraph.org/s2008/

URL for downloading the paper:

http://www.mpi-inf.mpg.de/resources/perfcap/pcmv_preprint.pdf

Event Address*:

Los Angeles, USA

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

11 August 2008

Event End Date:

15 August 2008

Publisher

Name*:

ACM

URL:

http://www.acm.org/

Address*:

New York, USA

Type:


Vol, No, Year, pp.

Series:

ACM Transactions on Graphics

Volume:

27(3)

Number:

3

Month:


Pages:

1-10

Year*:

2008

VG Wort Pages:


ISBN/ISSN:


Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

This paper proposes a new marker-less approach to capturing human performances from multi-view video. Our algorithm can jointly reconstruct spatio-temporally coherent geometry, motion and textural surface appearance of actors that perform complex and rapid moves. Furthermore, since our algorithm is purely meshbased and makes as few as possible prior assumptions about the type of subject being tracked, it can even capture performances of people wearing wide apparel, such as a dancer wearing a skirt. To serve this purpose our method efficiently and effectively combines the power of surface- and volume-based shape deformation techniques with a new mesh-based analysis-through-synthesis framework. This framework extracts motion constraints from video and makes the laser-scan of the tracked subject mimic the recorded performance. Also small-scale time-varying shape detail is recovered by applying model-guided multi-view stereo to refine the model surface. Our method delivers captured performance data at higher level of detail, is highly versatile, and is applicable to many complex types of scenes that could not be handled by alternative marker-based or marker-free recording techniques.

HyperLinks / References / URLs:

http://www.mpi-inf.mpg.de/resources/perfcap/



Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Audience:

experts only

Appearance:

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



BibTeX Entry:

@INPROCEEDINGS{deAguiar2008,
AUTHOR = {de Aguiar, Edilson and Stoll, Carsten and Ahmed, Naveed and Seidel, Hans-Peter},
EDITOR = {Turk, Greg},
TITLE = {Performance Capture from Sparse Multi-View Video},
BOOKTITLE = {Proceedings of ACM SIGGRAPH 2008},
PUBLISHER = {ACM},
YEAR = {2008},
NUMBER = {3},
VOLUME = {27(3)},
PAGES = {1--10},
SERIES = {ACM Transactions on Graphics},
ADDRESS = {Los Angeles, USA},
}


Entry last modified by Thomas Schultz, 07/01/2009
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Editor(s)
Carsten Stoll
Created
02/05/2009 02:21:51 PM
Revision
1.
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Editor
Thomas Schultz
Carsten Stoll


Edit Date
03/19/2009 05:38:33 PM
02/05/2009 02:21:51 PM


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