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SA-Optimized Multiple View Smooth Polyhedron Representation NN

  • Mohamad Ivan Fanany
  • Itsuo Kumazawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2843)

Abstract

Simulated Annealing (SA) is a powerful stochastic search method that can produce very high quality solutions for hard combinatorial optimization problem. In this paper, we applied this SA method to optimize our 3D hierarchical reconstruction neural network (NN). This NN deals with complicated task to reconstruct a complete representation of a given object relying only on a limited number of views and erroneous depth maps of shaded images. The depth maps are obtained by Tsai-Shah shape-from-shading (SFS) algorithm. The experimental results show that the SA optimization enable our reconstruction system to escape from a local minima. Hence, it gives more exact and stable results with small additional computation time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Mohamad Ivan Fanany
    • 1
  • Itsuo Kumazawa
    • 1
  1. 1.Imaging Science and EngineeringTokyo Institute of Technology 

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