Voxel-Space Ambient Occlusion

Abstract

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Ambient occlusion adds important detail to a scene. This paper presents a multiresolution screen-space voxel based ambient occlusion technique, which improves G-buffer based techniques, avoiding artifacts such as haloing. Our technique is scalable to the level-of-detail desired by the user. REPORT DATE (DD-MM-YYYY)4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES The views, opinions and/or findings contained in this report are those of the author(s) and should not contrued as an official Department of the Army position, policy or decision, unless so designated by other documentation. DISTRIBUTION AVAILIBILITY STATEMENTApproved for public release; distribution is unlimited. Because we assume voxels to be small objects, we compute ambient occlusion using an area rendering equation based formulation. As ambient occlusion changes smoothly across a scene, we use a stencil based screen-space multiresolution buffer to refine and render multiple resolution images. Curvature and depth discontinuity metrics to identify appropriate sampling rates. Abstract Ambient occlusion adds important detail to a scene. This paper presents a multiresolution screen-space voxel based ambient occlusion technique, which improves G-buffer based techniques, avoiding artifacts such as haloing. Our technique is scalable to the level-of-detail desired by the user. UU SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)6 Voxel-Space Ambient OcclusionBecause we assume voxels to be small objects, we compute ambient occlusion using an area rendering equation based formulation. As ambient occlusion changes smoothly across a scene, we use a stencil based screen-space multiresolution buffer to refine and render multiple resolution images. Curvature and depth discontinuity metrics to identify appropriate sampling rates.

DeepAO: Efficient Screen Space Ambient Occlusion Generation via Deep Network

“…Besides of SSAO and VAO, Penmatsa et al propose the VXAO method in [24]. Instead of relying on screen space data, this method gathers information from a world space in voxel representation of the scene, which covers a large area around the viewer.…”