Hardware Accelerated Ambient Occlusion Techniques on GPUs

We introduce an approximate yet visually pleasant ambient occlusion approximation running on real-time graphics hardware. Our method is a multi-pass algorithm that separates the ambient occlusion problem into high-frequency, detailed ambient occlusion and low-frequency, distant ambient occlusion domains, both capable of running independently and in parallel. The high-frequency detailed approach uses an image-space approach to approximate the ambient occlusion due to nearby occluders due to high surface detail. The low-frequency approach uses the intrinsic properties of a modern GPU to greatly reduce the search area for large and distant occluders with the help of a low-detail approximated version of the occluder geometry. Our current results show a promising trend in utilizing the highly parallel, stream processors (GPUs) to perform real-time visually pleasant ambient occlusion. We show that our ambient occlusion solution works on a wide variety of applications such as molecular data visualization, dynamic deformable animated models, highly detailed geometry. Our algorithm demonstrates scalability using a multi-GPU environment, and is Direct3D 10-aware in many respects, allowing for a smooth adaptation to the anticipated fundamental changes in upcoming graphics hardware.