An inverse problem approach for automatically adjusting the parameters for rendering clouds using photographs
ACM Trans. Graph.(2012)
Abstract
Clouds play an important role in creating realistic images of outdoor scenes. Many methods have therefore been proposed for displaying realistic clouds. However, the realism of the resulting images depends on many parameters used to render them and it is often difficult to adjust those parameters manually. This paper proposes a method for addressing this problem by solving an inverse rendering problem: given a non-uniform synthetic cloud density distribution, the parameters for rendering the synthetic clouds are estimated using photographs of real clouds. The objective function is defined as the difference between the color histograms of the photograph and the synthetic image. Our method searches for the optimal parameters using genetic algorithms. During the search process, we take into account the multiple scattering of light inside the clouds. The search process is accelerated by precomputing a set of intermediate images. After ten to twenty minutes of precomputation, our method estimates the optimal parameters within a minute.
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Key words
synthetic cloud,inverse problem approach,synthetic image,method search,realistic image,optimal parameter,inverse rendering problem,search process,color histogram,realistic cloud,non-uniform synthetic cloud density,inverse problem
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