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  Motion Capture Using Joint Skeleton Tracking and Surface Estimation

Gall, J., Stoll, C., de Aguiar, E., Theobalt, C., Rosenhahn, B., & Seidel, H.-P. (2009). Motion Capture Using Joint Skeleton Tracking and Surface Estimation. In 2009 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1746-1753). Los Alamitos: IEEE Computer Society.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-19BF-8 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-5957-C
Genre: Conference Paper

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© IEEE, 2009. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 10.1109/CVPR.2009.5206755.
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 Creators:
Gall, Jürgen1, Author           
Stoll, Carsten1, Author           
de Aguiar, Edilson1, Author           
Theobalt, Christian1, Author                 
Rosenhahn, Bodo1, Author           
Seidel, Hans-Peter1, Author                 
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: This paper proposes a method for capturing the performance of a human or
an animal from a multi-view video sequence. Given an articulated
template model and silhouettes from a multi-view image sequence, our
approach recovers not only the movement of the skeleton, but also the
possibly non-rigid temporal deformation of the 3D surface.
While large scale deformations or fast movements are captured by the skeleton
pose and approximate surface skinning, true small scale deformations or
non-rigid garment motion are captured by fitting the surface to
the silhouette. We further
propose a novel optimization scheme for skeleton-based pose estimation
that exploits the skeleton's tree structure to split the
optimization problem into a local one and a lower dimensional global one.
We show on various sequences that our approach can capture the 3D motion of
animals and humans accurately even in the case of rapid movements and
wide apparel like skirts.

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Language(s): eng - English
 Dates: 2009-03-242009
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 520480
Other: Local-ID: C125675300671F7B-76CFE158D6F5470BC1257583005FD867-Gall2009b
BibTex Citekey: Gall-et-al_CVPR09
DOI: 10.1109/CVPR.2009.5206755
 Degree: -

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Title: 2009 IEEE Conference on Computer Vision and Pattern Recognition
Place of Event: Miami, FL, USA
Start-/End Date: 2009-06-20 - 2009-06-25

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Title: 2009 IEEE Conference on Computer Vision and Pattern Recognition
  Abbreviation : CVPR 2009
Source Genre: Proceedings
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Publ. Info: Los Alamitos : IEEE Computer Society
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1746 - 1753 Identifier: ISBN: 978-1-4244-3992-8