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ABSTRACT
We describe a method for the acquisition of deformable human geometry from silhouettes. Our technique uses a commercial tracking system to determine the motion of the skeleton, then estimates geometry for each bone using constraints provided by the silhouettes from one or more cameras. These silhouettes do not give a complete characterization of the geometry for a particular point in time, but when the subject moves, many observations of the same local geometries allow the construction of a complete model. Our reconstruction algorithm provides a simple mechanism for solving the problems of view aggregation, occlusion handling, hole filling, noise removal, and deformation modeling. The resulting model is parameterized to synthesize geometry for new poses of the skeleton. We demonstrate this capability by rendering the geometry for motion sequences that were not included in the original datasets.
REFERENCES
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CITED BY 20
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Michael Wand , Philipp Jenke , Qixing Huang , Martin Bokeloh , Leonidas Guibas , Andreas Schilling, Reconstruction of deforming geometry from time-varying point clouds, Proceedings of the fifth Eurographics symposium on Geometry processing, July 04-06, 2007, Barcelona, Spain
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Matthew Flagg , Atsushi Nakazawa , Qiushuang Zhang , Sing Bing Kang , Young Kee Ryu , Irfan Essa , James M. Rehg, Human video textures, Proceedings of the 2009 symposium on Interactive 3D graphics and games, February 27-March 01, 2009, Boston, Massachusetts
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Michael Wand , Bart Adams , Maksim Ovsjanikov , Alexander Berner , Martin Bokeloh , Philipp Jenke , Leonidas Guibas , Hans-Peter Seidel , Andreas Schilling, Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data, ACM Transactions on Graphics (TOG), v.28 n.2, p.1-15, April 2009
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