Surface reconstruction from images using a variational formulation

  • Authors:
  • Liuxin Zhang;Yunde Jia

  • Affiliations:
  • Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, P.R. China;Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, P.R. China

  • Venue:
  • MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
  • Year:
  • 2010

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Abstract

In this paper, we present a new approach to recovering the surface of a 3D object from multiple calibrated images. The method is based on a variational formulation which defines an energy functional where both silhouette and texture consistency constraints are included. We cast the surface reconstruction problem as an optimization of the energy functional amenable for minimization with an Euler-Lagrange driven evolution. Starting from an initial surface, the reconstruction result can be obtained at the end of the evolution. Compared to the traditional reconstruction methods using a variational framework, our method can be easily implemented by simple finite difference scheme and is computationally more efficient. The final result of our method is not sensitive to where the initial surface has started its evolution.