Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 |
| Herausgeber (Verlag) | IEEE Computer Society |
| Seiten | 1746-1753 |
| Seitenumfang | 8 |
| ISBN (Print) | 9781424439935 |
| Publikationsstatus | Veröffentlicht - 2009 |
| Veranstaltung | 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Miami, FL, USA / Vereinigte Staaten Dauer: 20 Juni 2009 → 25 Juni 2009 |
Publikationsreihe
| Name | 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 |
|---|---|
| Band | 2009 IEEE Computer Society Conference on Computer Vision and ... |
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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Ingenieurwesen (insg.)
- Biomedizintechnik
Zitieren
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- Harvard
- Apa
- Vancouver
- BibTex
- RIS
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009. IEEE Computer Society, 2009. S. 1746-1753 5206755 (2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009; Band 2009 IEEE Computer Society Conference on Computer Vision and ...).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Motion capture using joint skeleton tracking and surface estimation
AU - Gall, Juergen
AU - Stoll, Carsten
AU - De Aguiar, Edilson
AU - Theobalt, Christian
AU - Rosenhahn, Bodo
AU - Seidel, Hans Peter
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=70450199826&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2009.5206755
DO - 10.1109/CVPRW.2009.5206755
M3 - Conference contribution
AN - SCOPUS:70450199826
SN - 9781424439935
T3 - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
SP - 1746
EP - 1753
BT - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
PB - IEEE Computer Society
T2 - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Y2 - 20 June 2009 through 25 June 2009
ER -