scholarly journals A Corner-Highlighting Method for Ambient Occlusion

2021 ◽  
Vol 11 (7) ◽  
pp. 3276
Author(s):  
Sukjun Park ◽  
Nakhoon Baek

Graphical user experiences are now ubiquitous features, and therefore widespread. Specifically, the computer graphics field and the game industry have been continually favoring the ambient occlusion post-processing method for its superb indirect light approximation and its effectiveness. Nonetheless of its canonical performance, its operation on non-occluded surfaces is often seen redundant and unfavorable. In this paper, we propose a new perspective to handle such issues by highlighting the corners where ambient occlusion is likely to occur. Potential illumination occlusions are highlighted by checking the corners of the surfaces in the screen-space. Our algorithm showed feasibility for renderers to avoid unwanted computations by achieving performance improvements of 15% to 28% acceleration, in comparison to the previous works.

Author(s):  
Jop Vermeer ◽  
Leonardo Scandolo ◽  
Elmar Eisemann

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.


1990 ◽  
Vol 25 (12) ◽  
pp. 1355
Author(s):  
S. S. Winkler ◽  
Y. H. Kao ◽  
J. A. Sorenson

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