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  VolumeDeform: Real-time Volumetric Non-rigid Reconstruction

Innmann, M., Zollhöfer, M., Nießner, M., Theobalt, C., & Stamminger, M. (2016). VolumeDeform: Real-time Volumetric Non-rigid Reconstruction. Retrieved from http://arxiv.org/abs/1603.08161.

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arXiv:1603.08161.pdf (Preprint), 3MB
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 Urheber:
Innmann, Matthias1, Autor
Zollhöfer, Michael2, Autor           
Nießner, Matthias1, Autor           
Theobalt, Christian2, Autor           
Stamminger, Marc1, Autor           
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1External Organizations, ou_persistent22              
2Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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Schlagwörter: Computer Science, Computer Vision and Pattern Recognition, cs.CV
 Zusammenfassung: We present a novel approach for the reconstruction of dynamic geometric shapes using a single hand-held consumer-grade RGB-D sensor at real-time rates. Our method does not require a pre-defined shape template to start with and builds up the scene model from scratch during the scanning process. Geometry and motion are parameterized in a unified manner by a volumetric representation that encodes a distance field of the surface geometry as well as the non-rigid space deformation. Motion tracking is based on a set of extracted sparse color features in combination with a dense depth-based constraint formulation. This enables accurate tracking and drastically reduces drift inherent to standard model-to-depth alignment. We cast finding the optimal deformation of space as a non-linear regularized variational optimization problem by enforcing local smoothness and proximity to the input constraints. The problem is tackled in real-time at the camera's capture rate using a data-parallel flip-flop optimization strategy. Our results demonstrate robust tracking even for fast motion and scenes that lack geometric features.

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Sprache(n): eng - English
 Datum: 2016-03-262016-07-302016
 Publikationsstatus: Online veröffentlicht
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 Identifikatoren: arXiv: 1603.08161
URI: http://arxiv.org/abs/1603.08161
BibTex Citekey: InnmannarXiv1603.08161
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