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  4. Capturing 3D Stretchable Surfaces from Single Images in Closed Form
 
conference paper

Capturing 3D Stretchable Surfaces from Single Images in Closed Form

Moreno-Noguer, Francesc
•
Salzmann, Mathieu
•
Lepetit, Vincent  
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2009
2009 IEEE Conference on Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition (CVPR)

We present a closed-form solution to the problem of re- covering the 3D shape of a non-rigid potentially stretchable surface from 3D-to-2D correspondences. In other words, we can reconstruct a surface from a single image without a priori knowledge of its deformations in that image. State-of-the-art solutions to non-rigid 3D shape recovery rely on the fact that distances between neighboring surface points must be preserved and are therefore limited to in- elastic surfaces. Here, we show that replacing the inextensibility constraints by shading ones removes this limitation while still allowing 3D reconstruction in closed-form. We demonstrate our method and compare it to an earlier one using both synthetic and real data.

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Type
conference paper
DOI
10.1109/CVPR.2009.5206758
Author(s)
Moreno-Noguer, Francesc
Salzmann, Mathieu
Lepetit, Vincent  
Fua, Pascal  
Date Issued

2009

Published in
2009 IEEE Conference on Computer Vision and Pattern Recognition
Start page

1842

End page

1849

Subjects

Deformable surface

•

3D reconstruction

•

monocular

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CVLAB  
Event name
Computer Vision and Pattern Recognition (CVPR)
Available on Infoscience
November 13, 2013
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/96997
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