Adaptively Layered Statistical Volumetric Obscurance

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dc.contributor.authorHendrick, Quintjinen_US
dc.contributor.authorScandolo, Leonardoen_US
dc.contributor.authorEisemann, Martinen_US
dc.contributor.authorEisemann, Elmaren_US
dc.contributor.editorPetrik Clarberg and Elmar Eisemannen_US
dc.date.accessioned2016-01-19T10:32:56Z
dc.date.available2016-01-19T10:32:56Z
dc.date.issued2015en_US
dc.description.abstractWe accelerate volumetric obscurance, a variant of ambient occlusion, and solve undersampling artifacts, such as banding, noise or blurring, that screen-space techniques traditionally suffer from. We make use of an efficient statistical model to evaluate the occlusion factor in screen-space using a single sample. Overestimations and halos are reduced by an adaptive layering of the visible geometry. Bias at tilted surfaces is avoided by projecting and evaluating the volumetric obscurance in tangent space of each surface point. We compare our approach to several traditional screen-space ambient obscurance techniques and show its competitive qualitative and quantitative performance. Our algorithm maps well to graphics hardware, does not require the traditional bilateral blur step of previous approaches, and avoids typical screen-space related artifacts such as temporal instability due to undersampling.en_US
dc.description.sectionheadersRendering and Displayen_US
dc.description.seriesinformationHigh-Performance Graphicsen_US
dc.identifier.doi10.1145/2790060.2790070en_US
dc.identifier.isbn978-1-4503-3707-6en_US
dc.identifier.pages77-84en_US
dc.identifier.urihttps://doi.org/10.1145/2790060.2790070en_US
dc.publisherACM Siggraphen_US
dc.subjectSSAOen_US
dc.subjectSummed Area Tablesen_US
dc.subjectglobal illuminationen_US
dc.titleAdaptively Layered Statistical Volumetric Obscuranceen_US
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High-Performance Graphics 2015