Importance Driven Environment Map Sampling.

Abstract

In this paper we present an efficient method for supporting image based lighting (IBL) for bidirectional methods. This improves both sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These parts of the scene often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves sampling efficiency, by taking into account view importance, and modifies the lighting distribution to use light transport information from the camera. This method automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling of light paths. This approach can be applied to several bidirectional rendering methods, and results are shown for bidirectional path tracing, metropolis light transport and progressive photon mapping. When compared to other methods, efficiency results demonstrate speed ups of orders of magnitude.