Hierarchical Image-Space Radiosity for Interactive Global Illumination

We introduce image-space radiosity and a hierarchical variant as a method for interactively approximating diffuse indirect illumination in fully dynamic scenes. As oft observed, diffuse indirect illumination contains mainly low-frequency details that do not require independent computations at every pixel. Prior work leverages this to reduce computation costs by clustering and caching samples in world or object space. This often involves scene preprocessing, complex data structures for caching, or wasted computations outside the view frustum. We instead propose clustering computations in image space, allowing the use of cheap hardware mipmapping and implicit quadtrees to allow coarser illumination computations. We build on a recently introduced multiresolution splatting technique combined with an image-space lightcut algorithm to intelligently choose virtual point lights for an interactive, one-bounce instant radiosity solution. Intelligently selecting point lights from our reflective shadow map enables temporally coherent illumination similar to results using more than 4096 regularly-sampled VPLs.     

Temporally Coherent Adaptive Sampling for Imperfect Shadow Maps

We propose a new adaptive algorithm for determining virtual point lights (VPL) in the scope of real‐time instant radiosity methods, which use a limited number of VPLs. The proposed method is based on Metropolis‐Hastings sampling and exhibits better temporal coherence of VPLs, which is particularly important for real‐time applications dealing with dynamic scenes. We evaluate the properties of the proposed method in the context of the algorithm based on imperfect shadow maps and compare it with the commonly used inverse transform method. The results indicate that the proposed technique can significantly reduce the temporal flickering artifacts even for scenes with complex materials and textures. Further, we propose a novel splatting scheme for imperfect shadow maps using hardware tessellation. This scheme significantly improves the rendering performance particularly for complex and deformable scenes. We thoroughly analyze the performance of the proposed techniques on test scenes with detailed materials, moving camera, and deforming geometry.     

Sorted Deferred Shading for Production Path Tracing

Ray‐traced global illumination (GI) is becoming widespread in production rendering but incoherent secondary ray traversal limits practical rendering to scenes that fit in memory. Incoherent shading also leads to intractable performance with production‐scale textures forcing renderers to resort to caching of irradiance, radiosity, and other values to amortize expensive shading. Unfortunately, such caching strategies complicate artist workflow, are difficult to parallelize effectively, and contend for precious memory. Worse, these caches involve approximations that compromise quality. In this paper, we introduce a novel path‐tracing framework that avoids these tradeoffs. We sort large, potentially out‐of‐core ray batches to ensure coherence of ray traversal. We then defer shading of ray hits until we have sorted them, achieving perfectly coherent shading and avoiding the need for shading caches.     

Anisotropic Radiance-Cache Splatting for Efficiently Computing High-Quality Global Illumination with Lightcuts

Computing global illumination in complex scenes is even with todays computational power a demanding task. In this work we propose a novel irradiance caching scheme that combines the advantages of two state-of-the-art algorithms for high-quality global illumination rendering: lightcuts , an adaptive and hierarchical instant-radiosity based algorithm and the widely used (ir)radiance caching algorithm for sparse sampling and interpolation of (ir)radiance in object space. Our adaptive radiance caching algorithm is based on anisotropic cache splatting, which adapts the cache footprints not only to the magnitude of the illumination gradient computed with light-cuts but also to its orientation allowing larger interpolation errors along the direction of coherent illumination while reducing the error along the illumination gradient. Since lightcuts computes the direct and indirect lighting seamlessly, we use a two-layer radiance cache, to store and control the interpolation of direct and indirect lighting individually with different error criteria. In multiple iterations our method detects cache interpolation errors above the visibility threshold of a pixel and reduces the anisotropic cache footprints accordingly. We achieve significantly better image quality while also speeding up the computation costs by one to two orders of magnitude with respect to the well-known photon mapping with (ir)radiance caching procedure.     

Interactive Global Illumination for Deformable Geometry in CUDA

Interactive global illumination for fully deformable scenes with dynamic relighting is currently a very elusive goal in the area of realistic rendering. In this work we propose a system that is based on explicit visibility calculations and which is highly efficient and scalable. The rendering equation defines the light exchange between surfaces, which we approximate by subsampling. By utilizing the power of modern parallel GPUs using the CUDA framework we achieve interactive frame rates. Since we update the global illumination continuously in an asynchronous fashion, we maintain interactivity at all times for moderately complex scenes. We show that we can achieve higher frame rates for scenes with moving light sources, diffuse indirect illumination and dynamic geometry than other current methods, while maintaining a high image quality.     

Guided Image Filtering for Interactive High‐quality Global Illumination

Interactive computation of global illumination is a major challenge in current computer graphics research. Global illumination heavily affects the visual quality of generated images. It is therefore a key attribute for the perception of photo‐realistic images. Path tracing is able to simulate the physical behaviour of light using Monte Carlo techniques. However, the computational burden of this technique prohibits interactive rendering times on standard commodity hardware in high‐quality. Trying to solve the Monte Carlo integration with fewer samples results in characteristic noisy images. Global illumination filtering methods take advantage of the fact that the integral for neighbouring pixels may be very similar. Averaging samples of similar characteristics in screen‐space may approximate the correct integral, but may result in visible outliers. In this paper, we present a novel path tracing pipeline based on an edge‐aware filtering method for the indirect illumination which produces visually more pleasing results without noticeable outliers. The key idea is not to filter the noisy path traced images but to use it as a guidance to filter a second image composed from characteristic scene attributes that do not contain noise by default. We show that our approach better approximates the Monte Carlo integral compared to previous methods. Since the computation is carried out completely in screen‐space it is therefore applicable to fully dynamic scenes, arbitrary lighting and allows for high‐quality path tracing at interactive frame rates on commodity hardware.     

Approximate Bias Compensation for Rendering Scenes with Heterogeneous Participating Media

In this paper we present a novel method for high‐quality rendering of scenes with participating media. Our technique is based on instant radiosity, which is used to approximate indirect illumination between surfaces by gathering light from a set of virtual point lights (VPLs). It has been shown that this principle can be applied to participating media as well, so that the combined single scattering contribution of VPLs within the medium yields full multiple scattering. As in the surface case, VPL methods for participating media are prone to singularities, which appear as bright “splotches” in the image. These artifacts are usually countered by clamping the VPLs' contribution, but this leads to energy loss within the short‐distance light transport. Bias compensation recovers the missing energy, but previous approaches are prohibitively costly. We investigate VPL‐based methods for rendering scenes with participating media, and propose a novel and efficient approximate bias compensation technique. We evaluate our technique using various test scenes, showing it to be visually indistinguishable from ground truth.     

Spatial Directional Radiance Caching

We present a new approach for accelerated global illumination computation in scenes with glossy surfaces. Our algorithm combines sparse illumination computation used in the radiance caching algorithm with BRDF importance sampling. To make this approach feasible, we extend the idea of lazy illumination evaluation, used in the caching approaches, from the spatial to the directional domain. Using importance sampling allows us to apply caching not only on low-gloss but also on shiny materials with high-frequency BRDFs, for which the radiance caching algorithm breaks down.     

Space-Time Hierarchical Radiosity with Clustering and Higher-Order Wavelets

We address in this paper the issue of computing diffuse global illumination solutions for animation sequences. The principal difficulties lie in the computational complexity of global illumination, emphasized by the movement of objects and the large number of frames to compute, as well as the potential for creating temporal discontinuities in the illumination, a particularly noticeable artifact. We demonstrate how space‐time hierarchical radiosity, i.e. the application to the time dimension of a hierarchical decomposition algorithm, can be effectively used to obtain smooth animations: first by proposing the integration of spatial clustering in a space‐time hierarchy; second, by using a higher‐order wavelet basis adapted for the temporal dimension. The resulting algorithm is capable of creating time‐dependent radiosity solutions efficiently.     

High‐Quality Screen‐Space Ambient Occlusion using Temporal Coherence

Ambient occlusion is a cheap but effective approximation of global illumination. Recently, screen‐space ambient occlusion (SSAO) methods, which sample the frame buffer as a discretization of the scene geometry, have become very popular for real‐time rendering. We present temporal SSAO (TSSAO), a new algorithm which exploits temporal coherence to produce high‐quality ambient occlusion in real time. Compared to conventional SSAO, our method reduces both noise as well as blurring artefacts due to strong spatial filtering, faithfully representing fine‐grained geometric structures. Our algorithm caches and reuses previously computed SSAO samples, and adaptively applies more samples and spatial filtering only in regions that do not yet have enough information available from previous frames. The method works well for both static and dynamic scenes.     

Real‐Time Indirect Illumination and Soft Shadows in Dynamic Scenes Using Spherical Lights

We present a method for rendering approximate soft shadows and diffuse indirect illumination in dynamic scenes. The proposed method approximates the original scene geometry with a set of tightly fitting spheres. In previous work, such spheres have been used to dynamically evaluate the visibility function to render soft shadows. In this paper, each sphere also acts as a low‐frequency secondary light source, thereby providing diffuse one‐bounce indirect illumination. The method is completely dynamic and proceeds in two passes: In a first pass, the light intensity distribution on each sphere is updated based on sample points on the corresponding object surface and converted into the spherical harmonics basis. In a second pass, this radiance information and the visibility are accumulated to shade final image pixels. The sphere approximation allows us to compute visibility and diffuse reflections of an object at interactive frame rates of over 20 fps for moderately complex scenes.     

Making Imperfect Shadow Maps View‐Adaptive: High‐Quality Global Illumination in Large Dynamic Scenes

We propose an algorithm to compute interactive indirect illumination in dynamic scenes containing millions of triangles. It makes use of virtual point lights (VPL) to compute bounced illumination and a point‐based scene representation to query indirect visibility, similar to Imperfect Shadow Maps (ISM). To ensure a high fidelity of indirect light and shadows, our solution is made view‐adaptive by means of two orthogonal improvements: First, the VPL distribution is chosen to provide more detail, that is, more dense VPL sampling, where these contribute most to the current view. Second, the scene representation for indirect visibility is adapted to ensure geometric detail where it affects indirect shadows in the current view.     

Multi‐Image Based Photon Tracing for Interactive Global Illumination of Dynamic Scenes

Image space photon mapping has the advantage of simple implementation on GPU without pre‐computation of complex acceleration structures. However, existing approaches use only a single image for tracing caustic photons, so they are limited to computing only a part of the global illumination effects for very simple scenes. In this paper we fully extend the image space approach by using multiple environment maps for photon mapping computation to achieve interactive global illumination of dynamic complex scenes. The two key problems due to the introduction of multiple images are 1) selecting the images to ensure adequate scene coverage; and 2) reliably computing ray‐geometry intersections with multiple images. We present effective solutions to these problems and show that, with multiple environment maps, the image‐space photon mapping approach can achieve interactive global illumination of dynamic complex scenes. The advantages of the method are demonstrated by comparison with other existing interactive global illumination methods.     

Global Illumination using Photon Ray Splatting

We present a novel framework for efficiently computing the indirect illumination in diffuse and moderately glossy scenes using density estimation techniques. Many existing global illumination approaches either quickly compute an overly approximate solution or perform an orders of magnitude slower computation to obtain high-quality results for the indirect illumination. The proposed method improves photon density estimation and leads to significantly better visual quality in particular for complex geometry, while only slightly increasing the computation time. We perform direct splatting of photon rays, which allows us to use simpler search data structures. Since our density estimation is carried out in ray space rather than on surfaces, as in the commonly used photon mapping algorithm, the results are more robust against geometrically incurred sources of bias. This holds also in combination with final gathering where photon mapping often overestimates the illumination near concave geometric features. In addition, we show that our photon splatting technique can be extended to handle moderately glossy surfaces and can be combined with traditional irradiance caching for sparse sampling and filtering in image space.     

Photon‐driven Irradiance Cache

We describe a global illumination method combining two well known techniques: photon mapping and irradiance caching. The photon mapping method has the advantage of being view independent but requires a costly additional rendering pass, called final gathering. As for irradiance caching, it is view‐dependent, irradiance is only computed and cached on surfaces of the scene as viewed by a single camera. To compute records covering the entire scene, the irradiance caching method has to be run for many cameras, which takes a long time and is a tedious task since the user has to place the needed cameras manually. Our method exploits the advantages of these two methods and avoids any intervention of the user. It computes a refined, view‐independent irradiance cache from a photon map. The global illumination solution is then rendered interactively using radiance cache splatting.     

Improved Stochastic Progressive Photon Mapping with Metropolis Sampling

This paper presents an improvement to the stochastic progressive photon mapping (SPPM), a method for robustly simulating complex global illumination with distributed ray tracing effects. Normally, similar to photon mapping and other particle tracing algorithms, SPPM would become inefficient when the photons are poorly distributed. An inordinate amount of photons are required to reduce the error caused by noise and bias to acceptable levels. In order to optimize the distribution of photons, we propose an extension of SPPM with a Metropolis‐Hastings algorithm, effectively exploiting local coherence among the light paths that contribute to the rendered image. A well‐designed scalar contribution function is introduced as our Metropolis sampling strategy, targeting at specific parts of image areas with large error to improve the efficiency of the radiance estimator. Experimental results demonstrate that the new Metropolis sampling based approach maintains the robustness of the standard SPPM method, while significantly improving the rendering efficiency for a wide range of scenes with complex lighting.     

Precomputed Radiance Transfer Field for Rendering Interreflections in Dynamic Scenes

In this paper, we introduce a new representation – radiance transfer fields (RTF) – for rendering interreflections in dynamic scenes under low frequency illumination. The RTF describes the radiance transferred by an individual object to its surrounding space as a function of the incident radiance. An important property of RTF is its independence of the scene configuration, enabling interreflection computation in dynamic scenes. Secondly, RTFs naturally fit in with the rendering framework of precomputed shadow fields, incurring negligible cost to add interreflection effects. In addition, RTFs can be used to compute interreflections for both diffuse and glossy objects. We also show that RTF data can be highly compressed by clustered principal component analysis (CPCA), which not only reduces the memory cost but also accelerates rendering. Finally, we present some experimental results demonstrating our techniques.     

Adaptive Interleaved Sampling for Interactive High‐Fidelity Rendering

Recent advances have made interactive ray tracing (IRT) possible on consumer desktop machines. These advances have brought about the potential for interactive global illumination (IGI) with enhanced realism through physically based lighting. IGI, unlike IRT, has a much higher computational complexity. Furthermore, since non‐primary rays constitute the majority of the computation, the rays are predominantly incoherent, making impractical many of the methods that have made IRT possible. Two methods that have already shown promise in decreasing the computational time of the GI solution are interleaved sampling and adaptive rendering. Interleaved sampling is a generalized sampling scheme that smoothly blends between regular and irregular sampling while maintaining coherence. Adaptive rendering algorithms adjust rendering quality, non‐uniformally, using a guidance scheme. While adaptive rendering has shown to provide speed‐up when used for off‐line rendering it has not been utilized in IRT due to its naturally incoherent nature. In this paper, we combine adaptive rendering and interleaved sampling within a component‐based solution into a new approach we term adaptive interleaved sampling. This allows us to tailor new adaptive heuristics for interleaved sampling of the individual components of the GI solution significantly improving overall performance. We present a novel component‐based IGI framework for which we achieve interactive frame rates for a range of effects such as indirect diffuse lighting, soft shadows and single scatter homogeneous participating media.     

A Significance Cache for Accelerating Global Illumination

Rendering using physically based methods requires substantial computational resources. Most methods that are physically based use straightforward techniques that may excessively compute certain types of light transport, while ignoring more important ones. Importance sampling is an effective and commonly used technique to reduce variance in such methods. Most current approaches for physically based rendering based on Monte Carlo methods sample the BRDF and cosine term, but are unable to sample the indirect illumination as this is the term that is being computed. Knowledge of the incoming illumination can be especially useful in the case of hard to find light paths, such as caustics or scenes which rely primarily on indirect illumination. To facilitate the determination of such paths, we propose a caching scheme which stores important directions, and is analytically sampled to calculate important paths. Results show an improvement over BRDF sampling and similar illumination importance sampling.     

An Error Estimation Framework for Many‐Light Rendering

The popularity of many‐light rendering, which converts complex global illumination computations into a simple sum of the illumination from virtual point lights (VPLs), for predictive rendering has increased in recent years. A huge number of VPLs are usually required for predictive rendering at the cost of extensive computational time. While previous methods can achieve significant speedup by clustering VPLs, none of these previous methods can estimate the total errors due to clustering. This drawback imposes on users tedious trial and error processes to obtain rendered images with reliable accuracy. In this paper, we propose an error estimation framework for many‐light rendering. Our method transforms VPL clustering into stratified sampling combined with confidence intervals, which enables the user to estimate the error due to clustering without the costly computing required to sum the illumination from all the VPLs. Our estimation framework is capable of handling arbitrary BRDFs and is accelerated by using visibility caching, both of which make our method more practical. The experimental results demonstrate that our method can estimate the error much more accurately than the previous clustering method.