Ambient Occlusion Research Articles

Approximating global illumination with ambient occlusion and environment light via generative adversarial networks

Calculating global illumination in computer graphics is difficult, especially for complex scenes. This is due to the interreflections of the rays of light and the interactions with the materials of the objects composing the scene. Solutions based on ambient light approximations have been implemented. However, these are computationally intensive and produce images with less precision, as these solutions ignore the ambient lighting component by adopting coarse approximations. In this paper, we propose a method capable of approximating the global illumination effect. Our idea is to compute the global illumination by adding three images (direct illumination, environmental light, and ambient occlusion). Direct illumination is calculated by a reference method. Environmental illumination is computed using an adversarial neural network from a single 2D image. Ambient occlusion is generated using conditional adversarial neural networks with an attention mechanism to pay more attention to the relevant image features during the training step. We use two image masks to keep the object’s position in the screen space, which allows efficient reconstruction of the final result. Our solution produces quality images compared to reference images and does not require any computation in the 3D scene or screen space.

Dental topography and dietary specialization in Papionini primates

Our understanding of primate adaptive evolution depends on appreciating the way in which dental functional morphology affects food processing. The Papionini tribe ofCercopithecoideaprimates shows great dietary versatility and ecological adaptations to resource seasonality across the African and Asian ecosystems, however, there are few studies focusing on the occlusal topography of the bilophodont teeth and the effect of tooth wear in the crown shape. Here, we explore the relationship between wear-related dental functional morphology and dietary ecological constraints within the Papionini. Three-dimensional (3D) polygonal meshes of the upper permanent molar row (M1-3) were obtained in a large papionine sample (838 specimens) of known dietary preferences including species from six genera (Cercocebus,Lophocebus,Macaca,Mandrillus,Papio, andTheropithecus). All the sample was classified in four diet categories and four topographic metrics (orientation patch count rotated, OPCR; Dirichlet normal energy, DNE; occlusal relief, OR; and ambient occlusion, portion de ciel visible, PCV) were measured for each tooth-type according to wear stage (lightly and moderately worn) to determine diet-related interspecific morphological changes with long-term functionality. The results indicate that hard-object feeders (CercocebusandLophocebus) and grass eaters (Theropithecus gelada) exhibit a pattern of occlusal complexity (OPCR), surface curvature (DNE), relief (OR), and morphological wear resistance (PCV) that is significantly different from the omnivores and folivore-frugivore species (MandrillusandMacaca) despite the overall homogeneity of the bilophodont dentition. A multifactorial ANOVA showed that the topographic metrics were sensitive to tooth wear as expected. The results also indicate that the interspecific variability of dental topography of the upper molars reflects dietary specializations rather than phylogenetic proximity. These findings support the hypothesis that evolutionary convergence processes could have affected the Papionini, clustering the hard-object feeders (LophocebusandCercocebus)together in the morphospace, and clearly discriminating this group from the graminivorous and frugivores-folivores.

Screen space indirect lighting with visibility bitmask

Horizon-based indirect illumination efficiently estimates a diffuse light bounce in screen space by analytically integrating the horizon angle difference between samples along a given direction. Like other horizon-based methods, this technique cannot properly simulate light passing behind thin surfaces. We propose the concept of a visibility bitmask that replaces the two horizon angles by a bit field representing the binary state (occluded / un-occluded) of N sectors uniformly distributed around the hemisphere slice. It allows light to pass behind surfaces of constant thickness while keeping the efficiency of horizon-based methods. It can also do more accurate ambient lighting than bent normal by sampling more than one visibility cone. This technique improves the visual quality of ambient occlusion, indirect diffuse, and ambient light compared to previous screen space methods while minimizing noise and keeping a low performance overhead.

Photogrammetry-Based Volume Measurement Framework for the Particle Density Estimation of LECA.

This paper presents a photogrammetry-based volume measurement framework for the particle density estimation of Lightweight expanded clay aggregate (LECA). The results are compared with computed tomography (CT) and Archimedes’ method measurements. All of the steps required in order to apply the proposed approach are explained. Next, we discuss how the interpretation of open pores affects the results of volume measurements. We propose to process the shapes obtained from different methods by applying an Ambient Occlusion algorithm with the same threshold, t = 0.175. The difference between the CT and SfM methods is less than 0.006 g/cm3, proving that the photogrammetry-based approach is accurate enough. The Archimedes’ method significantly overestimates the density of the particles. Nevertheless, its accuracy is acceptable for most engineering purposes. Additionally, we evaluate the accuracy of shape reconstruction (in terms of the Hausdorff distance). For 95% of the grain’s surface, the maximum error is between 0.073 mm and 0.129 mm (depending on the grain shape). The presented approach is helpful for measuring the particle density of porous aggregates. The proposed methodology can be utilized in order to estimate intergranular porosity, which is valuable information for the calibration of DEM models.

Accounting for Non-Uniform Ambient Lighting in Ray Traced Ambient Occlusion

Ambient occlusion is a popular method to enhance the visuals of real-time applications. The generally accepted equation assumes that incoming ambient lighting is uniform in the enclosing hemisphere around the surface point. This assumption does not always hold and can cause artifacts. With screen-space techniques the artifact may not be present, because of the lack of information, but it becomes visible with more accurate methods. This is especially true for ray tracing based implementations which are widely used to create the ground truth image to measure other techniques. With recent advancements of the graphics hardware, they also found their way into real-time applications where these shortcomings were neither discussed nor addressed. In this paper we analyze the problem and demonstrate its presence in popular game engines. We also propose a ray tracing based extension to eliminate these artifact in a physically plausible way.

Stereo-consistent screen-space ambient occlusion

Screen-space ambient occlusion (SSAO) shows high efficiency and is widely used in real-time 3D applications. However, using SSAO algorithms in stereo rendering can lead to inconsistencies due to the differences in the screen-space information captured by the left and right eye. This will affect the perception of the scene and may be a source of viewer discomfort. In this paper, we show that the raw obscurance estimation part and subsequent filtering are both sources of inconsistencies. We developed a screen-space method involving both views in conjunction, leading to a stereo-aware raw obscurance estimation method and a stereo-aware bilateral filter. The results show that our method reduces stereo inconsistencies to a level comparable to geometry-based AO solutions, while maintaining the performance benefits of a screen-space approach.

MaterIA: Single Image High‐Resolution Material Capture in the Wild

AbstractWe propose a hybrid method to reconstruct a physically‐based spatially varying BRDF from a single high resolution picture of an outdoor surface captured under natural lighting conditions with any kind of camera device. Relying on both deep learning and explicit processing, our PBR material acquisition handles the removal of shades, projected shadows and specular highlights present when capturing a highly irregular surface and enables to properly retrieve the underlying geometry. To achieve this, we train two cascaded U‐Nets on physically‐based materials, rendered under various lighting conditions, to infer the spatially‐varying albedo and normal maps. Our network processes relatively small image tiles (512 × 512pixels) and we propose a solution to handle larger image resolutions by solving a Poisson system across these tiles. We complete this pipeline with analytical solutions to reconstruct height, roughness and ambient occlusion.

AOGAN: A generative adversarial network for screen space ambient occlusion

Ambient 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.

Embedding QR Code onto Triangulated Meshes using Horizon Based Ambient Occlusion

AbstractQR code is a widely used format to encode information through images that can be easily decoded using a smartphone. These devices play a significant role in most people's everyday lives, making the encoded information widely accessible. However, decoding the QR code becomes challenging when significant deformations occur in the label. An easy and quick solution to keep the deformation on a minimum level is to affix the label that contains the QR code onto a developable surface patch of a 3D model. The perspective distortion that can appear is efficiently dealt with during the decoding process. In recent years an alternative method has emerged. In the work of Kikuchi et al., the QR code is embedded onto B‐spline surfaces of CAD models to give more freedom in providing additional information. This method was further improved and extended by Peng et al. embed QR codes onto the surface of general meshes. This paper introduces a solution to embed QR codes onto the surface of general meshes without densely triangulating the selected area of the QR code. It uses the deferred shading technique to extract the surface normals and the depth values around the QR code's user‐given centre. We propose two methods for automatically finding the projection direction even when highly curved areas are selected based on the retrieved information while rendering the model. Besides, we introduce two methods needing a projection direction and a QR code centre to determine a size for automatically embedding the QR code. We propose patterns for decreasing the carving depth of the embedded QR codes, and we use the Horizon‐Based Ambient Occlusion to speed up the engraving process. We validate our method by comparing our results to the outcomes of Peng et al.

Feature-based clustered geometry for interpolated Ray-casting

Acceleration techniques for Rendering in general, and Ray-Casting in particular, have been the subject of much research in Computer Graphics. Most efforts have been focused on new data structures for efficient ray/scene traversal and intersection. In this paper, we propose an acceleration technique that approximates rendering and that is built around a new feature-based clustering approach. The technique starts preprocessing the scene by grouping elements according to their features using a set of channels based on an information theory-based approach. Then, at run-time, a rendering strategy uses that clustering information to reconstruct the final image, by deciding which areas could take advantage of the coherence in the features and thus, could be interpolated; and which areas require more involved calculations. This process starts with a low-resolution render that is iteratively refined up to the desired resolution by reusing previously computed pixels. Our experimental results show a significant speedup of an order of magnitude, depending on the complexity of the per-pixel calculations, the screen size of the objects, and the number of clusters. Rendering quality and speed directly depend on the number of clusters and the number of steps performed during the reconstruction procedure, and both can easily be set by the user. Our findings show that feature-based clustering can significantly impact rendering speed if samples are chosen to enable interpolation of smooth regions. Our technique, thus, accelerates a range of popular and costly techniques, ranging from texture mapping up to complex ambient occlusion, soft and hard shadow calculations, and it can even be used in conjunction with more traditional acceleration methods.

Approximate Image-Space Multidirectional Occlusion Shading Model for Direct Volume Rendering

Understanding and perceiving three-dimensional scientific visualizations, such as volume rendering, benefit from visual cues produced by the shading models. The conventional approaches are local shading models since they are computationally inexpensive and straightforward to implement. However, the local shading models do not always provide proper visual cues since non-local information is not sufficiently taken into account for the shading. Global illumination models achieve better visual cues, but they are often computationally expensive. It has been shown that alternative illumination models, such as ambient occlusion, multidirectional shading, and shadows, provide decent perceptual cues. Although these models improve upon local shading models, they still require expensive preprocessing, extra GPU memory, and a high computational cost, which cause a lack of interactivity during the transfer function manipulations and light position changes. In this paper, we proposed an approximate image-space multidirectional occlusion shading model for the volume rendering. Our model was computationally less expensive compared to the global illumination models and did not require preprocessing. Moreover, interactive transfer function manipulations and light position changes were achievable. Our model simulated a wide range of shading behaviors, such as ambient occlusion and soft and hard shadows, and can be effortlessly applied to existing rendering systems such as direct volume rendering. We showed that the suggested model enhanced the visual cues with modest computational costs.

Stochastic-Depth Ambient Occlusion

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.

Documenting carved stones from 3D models. Part II — Ambient occlusion to reveal carved parts

Revealing carved parts in rock art is of primary importance and remains a major challenge for archaeological documentation. Computational geometry applied to 3D imaging provides a unique opportunity to document rock art. This study evaluates five algorithms and derivatives used to compute ambient occlusion and sky visibility on 3D models of Mongolian stelae, also known as deer stones. By contrast with the previous companion work, models are processed directly in 3D, without preliminary projection. Volumetric obscurance gives the best results for the identification of carved figures. The effects of model resolution and parameters specific to ambient occlusion are then evaluated. Keeping tridimensional information intact allows accurate measurement of distance, volume, and depth. Objects augmented by ambient occlusion can easily be manipulated in 3D viewers, for seamless and effortless access to the overall organization of the figures, at the scale of the entire object. Qualitatively speaking, the 2D projected outputs are equivalent to, or even better than, existing archaeological documentation. The proposed workflow should be easily applicable in many situations, particularly as the functions provided for the free R programming software are fully configurable.

A Corner-Highlighting Method for Ambient Occlusion

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.

Advanced Rendering of Line Data with Ambient Occlusion and Transparency.

3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.

Deep Volumetric Ambient Occlusion

We present a novel deep learning based technique for volumetric ambient occlusion in the context of direct volume rendering. Our proposed Deep Volumetric Ambient Occlusion (DVAO) approach can predict per-voxel ambient occlusion in volumetric data sets, while considering global information provided through the transfer function. The proposed neural network only needs to be executed upon change of this global information, and thus supports real-time volume interaction. Accordingly, we demonstrate DVAOs ability to predict volumetric ambient occlusion, such that it can be applied interactively within direct volume rendering. To achieve the best possible results, we propose and analyze a variety of transfer function representations and injection strategies for deep neural networks. Based on the obtained results we also give recommendations applicable in similar volume learning scenarios. Lastly, we show that DVAO generalizes to a variety of modalities, despite being trained on computed tomography data only.

Chebyshev Ambient Occlusion

Ambient Occlusion (AO) is a widely used shadowing technique in 3D rendering. One of the main disadvantages of using it is that it requires not only the surface depth but also the normal vector, which usually causes severe aliasing. This work introduces a novel AO algorithm by applying Chebyshev’s inequality. Instead of requiring the normal vector, we process the mean ( $\mu $ ) of the distribution of depth values from the screen space. We can efficiently calculate the variance ( $\sigma ^{2}$ ) over any kernel region. Using the Chebyshev AO, we can get the upper bound on the percentage of the shaded surface that is occluded. Our proposed method can usually provide a good approximation of true occlusion and can be used as an approximate value for AO rendering. As a post-processing rending, the time complexity of Chebyshev AO is $O\left ({2k}\right)$ which is simple to implement on current graphics devices and can be applied to the next generation of ray tracing technology.

Rendering Optimization Approach for Game Engine Development

The article is devoted to the problem of creating a software tool for optimizing rendering in game engines, which will help users to quickly and easily configure their projects. The tool provides a centralized simple interface to the rendering tools built into a game engine. The key possibility of the tool is the management of visual effects, such as Bloom, Volumetric Shadow, Ambient Occlusion, etc. There is also an opportunity to use profilers and get a critical information for project optimization.

Comparative Analysis of Real-Time Global Illumination Techniques in Current Game Engines

The most important component of photorealism in Computer Graphics is given by a physically correct approximation of the light transport. Besides the direct illumination from light sources, there is an indirect illumination, produced by the reflections of the light rays on other surfaces of the scene. In Computer Graphics, the process of computing the illumination of a surface by considering both the direct and the indirect illumination is widely known as global illumination. This paper describes several classes of real-time global illumination techniques used in current game engines together with our own implementations of these approaches. All implementations were made in our own framework, specially designed with a multi-pass rendering architecture that allows fast implementation of rendering techniques and the reuse of functionalities. We analyze these classes based on the following criteria: the visual results produced by the indirect diffuse lighting, the ability to produce glossy reflections, shadows, ambient occlusion, subsurface scattering, translucency and volumetric lighting as well as the ability to simulate area lights. We present the quantitative results of our implementations, obtained with the same external parameters for all techniques, thanks to the unified implementations in the same framework. An important observation is that our analysis is focused on the techniques that are based on the rasterization pipeline, thus, the comparison does not include the techniques designed entirely for the ray-tracing pipeline.

An experimental study on volumetric visualization of black oil reservoir models

Volume rendering techniques are essential to inspect volume data. In this work, we consider volume rendering for unstructured meshes. We focus on the visualization of black oil reservoir simulation models, represented by irregular hexahedral meshes with geometry distortions and discontinuities. We conduct an experimental study comparing three different strategies to compute the volume integration. The first strategy resamples the model in a regular grid; the second linearizes the model geometry and the variation of the scalar field within a hexahedron cell; the third uses an accurate evaluation of the scalar field at each sample. We compare performance and image quality delivered by each strategy by running a set of experiments with different models. We also investigate the gain in perception applying directional ambient occlusion shading effects. All strategies were entirely implemented on the graphics card.