Abstract: A computer-implemented method of image generation that makes efficient use of reprojective techniques to reduce the cost of image generation. The method employs a technique of primitive reprojection in which convex graphics primitives are the reprojected elements. The visibility of elements known to be visible in a previous frame is first determined by transformation and depth-comparison rasterization of these elements. Regions of the image that may contain newly visible elements are located by occlusion-exposure transitions in the depth buffer and from incremental view volume motion. In these regions a depth-prioritized, data-access method of visible surface determination, spatial-subdivision ray casting, is employed to identify newly visible primitives which are added to the list of previously visible primitives for rasterization. The method employs a system of classifying objects based on their dynamic occlusive properties to increase the accuracy, efficiency and versatility of the reprojective approach.

Abstract: A computer implemented method of image generation that employs adaptive, progressive, perception-based spatio-temporal importance sampling to reduce the cost of image generation. The method uses an adaptive approach to sampling which employs refinement criteria based on specific spatio-temporal limits of human vision. By using these refinement criteria the method produces an image with a spatio-temporal structure that is closely matched to the spatio-temporal limits of human vision. Using one sampling criteria the spatial sampling density is adjusted in proportion to the sampled region's exposure duration in a manner that substantially reflects the visual systems's increase in acuity as a function of exposure time.