scholarly journals Optimization of screen-space directional occlusion algorithms

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 519-526 ◽  
Author(s):  
Marcin Wawrzonowski ◽  
Dominik Szajerman

Abstract Developers of video games and simulations from the day one have been trying to improve visuals of their products. The appearance of the scenes depends to a large extent on the approximation to the physical basis of light behaviour in the environments presented. The best effects in this regard are global illumination. However, it is too computationally expensive. One of the methods to simulate global illumination without a lot of processing is Screen-Space Ambient Occlusion. Many implementations of this technique were created, though few take into account direction and colour of the incoming light. An exception is a technique named SSDO – Screen-Space Directional Occlusion. Unfortunately, it suffers from the same drawbacks as its less realistic cousins, such as noise and banding while also remaining moderately expensive for computation. The main purpose of this paper is to optimize basic SSDO method using technique called Statistical Volumetric Obscurance, enhancing its performance while retaining plausible visual effect.

Author(s):  
Andrew Astapov ◽  
Vladimir Alexandrovich Frolov ◽  
Vladimir Alexandrovich Galaktionov

Screen-space Ambient Occlusion (SSAO) methods have become an integral part of the process of calculating global illumination effects in real-time applications. The use of ambient occlusion improves the perception of the geometry of the scene, and also makes a significant contribution to the realism of the rendered image. However, the problems of accuracy and efficiency of algorithms of calculating ambient occlusion remain relevant. Most of the existing methods have similar algorithmic complexity, what makes their use in real-time applications very limited. The performance issues of methods working in the screen space are particularly acute in the current growing spreadness of 4K (3840 x 2160 pixels) resolution of the rendered image. In this paper we provide our own algorithm Pyramid HBAO, which enhances the classic HBAO method by changing its calculation complexity for high resolution.


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.


2011 ◽  
Vol 10 (4) ◽  
pp. 61-65
Author(s):  
Robert Sajko ◽  
Zeljka Mihajlovic

The quality of computer rendering and perception of realism greatly depend on the shading method used to implement the interaction of light with the surfaces of objects in a scene. Ambient occlusion (AO) enhances the realistic impression of rendered objects and scenes. Properties that make Screen Space Ambient Occlusion (SSAO) interesting for real-time graphics are scene complexity independence, and support for fully dynamic scenes. However, there are also important issues with current approaches: poor texture cache use, introduction of noise, and performance swings. In this paper, a straightforward solution is presented. Instead of a traditional, geometry-based sampling method, a novel, image-based sampling method is developed, coupled with a revised heuristic function for computing occlusion. Proposed algorithm harnessing GPU power improves texture cache use and reduces aliasing artifacts. Two implementations are developed, traditional and novel, and their comparison reveals improved performance and quality of the proposed algorithm.


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