International Journal of Computer Vision

, Volume 66, Issue 2, pp 141–161

A Surface Reconstruction Method Using Global Graph Cut Optimization

Article

DOI: 10.1007/s11263-005-3953-x

Cite this article as:
Paris, S., Sillion, F.X. & Quan, L. Int J Comput Vision (2006) 66: 141. doi:10.1007/s11263-005-3953-x

Abstract

Surface reconstruction from multiple calibrated images has been mainly approached using local methods, either as a continuous optimization problem driven by level sets, or by discrete volumetric methods such as space carving. We propose a direct surface reconstruction approach which starts from a continuous geometric functional that is 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, existing stereo disparity methods are only interested in obtaining layers of constant disparity, while we focus on high resolution surface geometry. Second, most of the existing graph-cut algorithms only reach approximate solutions, while we guarantee a global minimum. The whole procedure is consistently incorporated into a voxel representation that handles both occlusions and discontinuities. We demonstrate our algorithm on real sequences, yielding remarkably detailed surface geometry up to 1/10th of a pixel.

Keywords

graph flow graph cut 3D reconstruction from calibrated cameras discontinuities self-occlusions occlusions global minimum 

Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  • Sylvain Paris
    • 1
  • François X. Sillion
    • 2
  • Long Quan
    • 3
  1. 1.MIT CSAILCambridgeUSA
  2. 2.ARTIS, GRAVIR/IMAG-INRIASaint IsmierFrance
  3. 3.Department of Computer ScienceHong Kong University of Science and TechnologyHong KongChina

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