Stochastic-Depth Ambient Occlusion

Journal Article (2021)
Author(s)

Jop Vermeer (Student TU Delft)

L. Scandolo (TU Delft - Computer Graphics and Visualisation)

E. Eisemann (TU Delft - Computer Graphics and Visualisation)

Research Group
Computer Graphics and Visualisation
Copyright
© 2021 Jop Vermeer, L. Scandolo, E. Eisemann
DOI related publication
https://doi.org/10.1145/3451268
More Info
expand_more
Publication Year
2021
Language
English
Copyright
© 2021 Jop Vermeer, L. Scandolo, E. Eisemann
Research Group
Computer Graphics and Visualisation
Issue number
1
Volume number
4
Pages (from-to)
3:1 - 3:15
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.

Files

SDAO.pdf
(pdf | 5.46 Mb)
License info not available