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A Surface Reconstruction Method Using Global Graph Cut Optimization

Sylvain Paris 1 François X. Sillion 2 Long Quan 3 
2 ARTIS - Acquisition, representation and transformations for image synthesis
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : The surface reconstruction from multiple calibrated images has been mainly approached using local methods, either as a continuous optimization driven by level sets, or as a discrete volumetric method of space carving. We here propose a direct surface reconstruction approach. It starts from a continuous geometric functional that is then minimized up to a discretization by a global graph-cut algorithm operating on a 3D embedded graph. The method is related to the stereo disparity computation based on graph-cut formulation, but fundamentally different in two aspects. First, the existing stereo disparity methods are only interested in obtaining layers of constant disparity, while we focus on a surface geometry of high resolution. Second, only approximate solutions are reached by most of the existing graph-cut algorithms, while we reach a global minimum. The whole procedure is consistently incorporated into a voxel representation that handles both occlusions and discontinuities. It is demonstrated on real sequences, yielding remarkably detailed surface geometry up to $1/10$th pixel.
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Submitted on : Wednesday, October 13, 2010 - 12:02:22 PM
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  • HAL Id : inria-00510219, version 1


Sylvain Paris, François X. Sillion, Long Quan. A Surface Reconstruction Method Using Global Graph Cut Optimization. International Journal of Computer Vision, 2006, 66 (2), pp.141--161. ⟨inria-00510219⟩



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