Screen Space Ambient Occlusion Based Multiple Importance Sampling for Real-Time Rendering

3D Research ◽  
2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Abd El Mouméne Zerari ◽  
Mohamed Chaouki Babahenini
Keyword(s):  
Real Time ◽  
Importance Sampling ◽  
Multiple Importance Sampling ◽  
Ambient Occlusion ◽  
Screen Space

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 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.

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.

Real-time Visual Tracking of Multiple Targets Using Bootstrap Importance Sampling

2012 ◽  
Vol 38 (10) ◽  
pp. 1663
Author(s):  
Le-Jun SHEN ◽  
Zhi-Sheng YOU ◽  
Xiao-Feng LI
Keyword(s):  
Real Time ◽  
Importance Sampling ◽  
Visual Tracking ◽  
Multiple Targets

scholarly journals Drone Ground Impact Footprints with Importance Sampling: Estimation and Sensitivity Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 3871
Author(s):  
Jérôme Morio ◽  
Baptiste Levasseur ◽  
Sylvain Bertrand
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Importance Sampling ◽  
Loss Of Control ◽  
Minimum Volume ◽  
Multiple Importance Sampling ◽  
Impact Position ◽  
Engine Failure ◽  
Main Engine ◽  
Ground Impact

This paper addresses the estimation of accurate extreme ground impact footprints and probabilistic maps due to a total loss of control of fixed-wing unmanned aerial vehicles after a main engine failure. In this paper, we focus on the ground impact footprints that contains 95%, 99% and 99.9% of the drone impacts. These regions are defined here with density minimum volume sets and may be estimated by Monte Carlo methods. As Monte Carlo approaches lead to an underestimation of extreme ground impact footprints, we consider in this article multiple importance sampling to evaluate them. Then, we perform a reliability oriented sensitivity analysis, to estimate the most influential uncertain parameters on the ground impact position. We show the results of these estimations on a realistic drone flight scenario.

REAL-TIME DISPERSIVE REFRACTION WITH ADAPTIVE SPECTRAL MAPPING

2013 ◽  
Vol 22 (06) ◽  
pp. 1360019
Author(s):  
DAMON BLANCHETTE ◽  
EMMANUEL AGU
Keyword(s):  
Real Time ◽  
White Light ◽  
Spectral Mapping ◽  
Mapping Algorithm ◽  
Physically Based ◽  
Refractive Medium ◽  
Interactive Frame ◽  
Screen Space ◽  
Special Case ◽  
Novel Algorithm

Spectral rendering, or the synthesis of images by taking into account the constituent wavelengths of white light, enables the rendering of iridescent colors caused by phenomena such as dispersion, diffraction, interference and scattering. Caustics, the focusing and defocusing of light through a refractive medium, can be interpreted as a special case of dispersion where all the wavelengths travel along the same paths. In this paper we extend Adaptive Caustic Mapping (ACM), a previously proposed caustics mapping algorithm, to handle physically-based dispersion. Because ACM can display caustics in real-time, it is amenable to extension to handle the more general case of dispersion. We also present a novel algorithm for filling in the gaps that occur due to discrete sampling of the spectrum. Our proposed method runs in screen-space, and is fast enough to display plausible dispersion phenomena at real-time and interactive frame rates.

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