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Geometry Construction from Caustic Images

  • Manuel Finckh
  • Holger Dammertz
  • Hendrik P. A. Lensch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6315)

Abstract

In this work we investigate an inverse geometry problem. Given a light source, a diffuse plane and a caustic image, how must a geometric object look like (transmissive or reflective) in oder to project the desired caustic onto the diffuse plane when lit by the light source? In order to construct the geometry we apply an analysis-by-synthesis approach, exploiting the GPU to accelerate caustic rendering based on the current geometry estimate. The optimization is driven by simultaneous perturbation stochastic approximation (SPSA). We confirm that this algorithm converges to the global minimum with high probability even in this ill-posed setting. We demonstrate results for precise geometry reconstruction given a caustic image and for reflector design producing an intended light distribution.

Keywords

Mean Square Error Stochastic Approximation Target Distribution Objective Function Evaluation Simultaneous Perturbation Stochastic Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Manuel Finckh
    • 1
  • Holger Dammertz
    • 1
  • Hendrik P. A. Lensch
    • 1
  1. 1.Institute of Media InformaticsUlm UniversityUlmGermany

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