Perceptually Guided Corrective Splatting

Abstract

One of the basic difficulties with interactive walkthroughs is the high quality rendering of object surfaces with non-diffuse light scattering characteristics. Since full ray tracing at interactive rates is usually impossible, we render a precomputed global illumination solution using graphics hardware and use remaining computational power to correct the appearance of non-diffuse objects on-the-fly. The question arises, how to obtain the best image quality as perceived by a human observer within a limited amount of time for each frame. We address this problem by enforcing corrective computation for those non-diffuse objects that are selected using a computational model of visual attention. We consider both the saliency- and task-driven selection of those objects and benefit from the fact that shading artifacts of "unattended" objects are likely to remain unnoticed. We use a hierarchical image-space sampling scheme to control ray tracing and splat the generated point samples. The resulting image converges progressively to a ray traced solution if the viewing parameters remain unchanged. Moreover, we use a sample cache to enhance visual appearance if the time budget for correction has been too low for some frame. We check the validity of the cached samples using a novel criterion suited for non-diffuse surfaces and reproject valid samples into the current view.