Sample distribution shadow maps

@inproceedings{Lauritzen2011SampleDS,
  title={Sample distribution shadow maps},
  author={Andrew Lauritzen and Marco Salvi and Aaron E. Lefohn},
  booktitle={SI3D},
  year={2011}
}
This paper introduces Sample Distribution Shadow Maps (SDSMs), a new algorithm for hard and soft-edged shadows that greatly reduces undersampling, oversampling, and geometric aliasing errors compared to other shadow map techniques. SDSMs fall into the space between scene-dependent, variable-performance shadow algorithms and scene-independent, fixed-performance shadow algorithms. They provide a fully automated solution to shadow map aliasing by optimizing the placement and size of a fixed number… CONTINUE READING

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