Shadow geometry maps for alias-free shadows

Abstract Shadow maps sample scene visibility in the light source space and offer an efficient solution to generate hard shadows. However, they suffer from aliasing artifacts because of discretization errors, inadequate resolution and projection distortion. In this paper, we propose the shadow geometry map method, where a shadow depth map is augmented by storing geometry information about scenes. This leads to a new shadow-rendering algorithm that combines a supersampling filter, a geometry-aware reconstruction kernel and an irreg-ular sampling filter. Our method produces high quality alias-free and subpixel supersampling shadow rendering and retains the simplicity and the efficiency of shadow maps. We show that the algorithm pipeline is efficiently parallelized using current programmable graphics hardware and that our method is capable of generating high quality hard shadows