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CVPR
2009
IEEE

Motion Capture Using Joint Skeleton Tracking and Surface Estimation

10 years 6 months ago
Motion Capture Using Joint Skeleton Tracking and Surface Estimation
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.
Juergen Gall (BIWI, ETH Zurich), Carsten Stoll (Ma
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Juergen Gall (BIWI, ETH Zurich), Carsten Stoll (Max Planck Institut Informatik), Edilson De Aguiar (Max Planck Institut Informatik), Christian Theobalt (Stanford University), Bodo Rosenhahn (University of Hannover), Hans-Peter Seidel (Max Planck Institut Informatik)
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