Filtered Stochastic Shadow Mapping Using a Layered Approach

Magnus Andersson
Lund University /
Intel Corporation

Jon Hasselgren
Intel Corporation

Jacob Munkberg
Intel Corporation

Tomas Akenine-Möller
Lund University /
Intel Corporation

To appear in Computer Graphics Forum 2015.

Abstract

Given a stochastic shadow map rendered with motion blur, our goal is to render an image from the eye with motion-blurred shadows with as little noise as possible. We use a layered approach in the shadow map and reproject samples along the average motion vector, and then perform lookups in this representation. Our results include substantially improved shadow quality compared to previous work and a fast graphics processing unit (GPU) implementation. In addition, we devise a set of scenes that are designed to bring out and show problematic cases for motion-blurred shadows. These scenes have difficult occlusion characteristics, and may be used in future research on this topic.

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An author generated version of the paper. [9MB pdf] bibtex

Test scenes

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