scholarly journals Pyramid HBAO — a Scalable Horizon-based Ambient Occlusion Method

2021 ◽  
Author(s):  
Andrew Astapov ◽  
Vladimir Alexandrovich Frolov ◽  
Vladimir Alexandrovich Galaktionov
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Significant Contribution ◽  
Global Illumination ◽  
Algorithmic Complexity ◽  
Ambient Occlusion ◽  
Efficiency Of Algorithms ◽  
Real Time Applications ◽  
Performance Issues ◽  
Screen Space

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.

scholarly journals Stochastic-Depth Ambient Occlusion

2021 ◽  
Vol 4 (1) ◽  
pp. 1-15
Author(s):  
Jop Vermeer ◽  
Leonardo Scandolo ◽  
Elmar Eisemann
Keyword(s):  
Real Time ◽  
High Performance ◽  
Depth Map ◽  
Visual Quality ◽  
Ambient Light ◽  
Missing Information ◽  
Time Performance ◽  
Ambient Occlusion ◽  
Depth Buffer ◽  
Screen Space

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.

scholarly journals Fast Image-Based Ambient Occlusion IBAO

2011 ◽  
Vol 10 (4) ◽  
pp. 61-65
Author(s):  
Robert Sajko ◽  
Zeljka Mihajlovic
Keyword(s):  
Real Time ◽  
Sampling Method ◽  
Dynamic Scenes ◽  
Heuristic Function ◽  
Ambient Occlusion ◽  
Improved Performance ◽  
Straightforward Solution ◽  
And Performance ◽  
Screen Space

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.

scholarly journals Pixelwise Phase Unwrapping Based on Ordered Periods Phase Shift

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 377
Author(s):  
Satoshi Tabata ◽  
Michika Maruyama ◽  
Yoshihiro Watanabe ◽  
Masatoshi Ishikawa
Keyword(s):  
High Resolution ◽  
Phase Shift ◽  
Real Time ◽  
High Precision ◽  
High Speed ◽  
Moving Objects ◽  
Global Illumination ◽  
Accurate Method ◽  
Phase Unwrapping ◽  
Order Structure

The existing phase-shift methods are effective in achieving high-speed, high-precision, high-resolution, real-time shape measurement of moving objects; however, a phase-unwrapping method that can handle the motion of target objects in a real environment and is robust against global illumination as well is yet to be established. Accordingly, a robust and highly accurate method for determining the absolute phase, using a minimum of three steps, is proposed in this study. In this proposed method, an order structure that rearranges the projection pattern for each period of the sine wave is introduced, so that solving the phase unwrapping problem comes down to calculating the pattern order. Using simulation experiments, it has been confirmed that the proposed method can be used in high-speed, high-precision, high-resolution, three-dimensional shape measurements even in situations with high-speed moving objects and presence of global illumination. In this study, an experimental measurement system was configured with a high-speed camera and projector, and real-time measurements were performed with a processing time of 1.05 ms and a throughput of 500 fps.

scholarly journals Optimization of screen-space directional occlusion algorithms

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 519-526 ◽  
Author(s):  
Marcin Wawrzonowski ◽  
Dominik Szajerman
Keyword(s):  
Video Games ◽  
Global Illumination ◽  
Physical Basis ◽  
Visual Effect ◽  
Ambient Occlusion ◽  
Computationally Expensive ◽  
Games And Simulations ◽  
Screen Space ◽  
Incoming Light

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.

scholarly journals AOGAN: A generative adversarial network for screen space ambient occlusion

2022 ◽  
Author(s):  
Lei Ren ◽  
Ying Song
Keyword(s):  
Light Intensity ◽  
Real Time ◽  
Generative Model ◽  
Attention Mechanism ◽  
Generative Adversarial Network ◽  
Learning Framework ◽  
Adversarial Network ◽  
Ambient Occlusion ◽  
Complex Scenes ◽  
Screen Space

AbstractAmbient occlusion (AO) is a widely-used real-time rendering technique which estimates light intensity on visible scene surfaces. Recently, a number of learning-based AO approaches have been proposed, which bring a new angle to solving screen space shading via a unified learning framework with competitive quality and speed. However, most such methods have high error for complex scenes or tend to ignore details. We propose an end-to-end generative adversarial network for the production of realistic AO, and explore the importance of perceptual loss in the generative model to AO accuracy. An attention mechanism is also described to improve the accuracy of details, whose effectiveness is demonstrated on a wide variety of scenes.

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