Real-time homogenous translucent material editing

This paper presents a novel method for real-time homogenous translucent material editing under fixed illumination. We consider the complete analytic BSSRDF model proposed by Jensen et al. [ [JMLH01] ], including both multiple scattering and single scattering. Our method allows the user to adjust the analytic parameters of BSSRDF and provides high-quality, real-time rendering feedback. Inspired by recently developed Precomputed Radiance Transfer (PRT) techniques, we approximate both the multiple scattering diffuse reflectance function and the single scattering exponential attenuation function in the analytic model using basis functions, so that re-computing the outgoing radiance at each vertex as parameters change reduces to simple dot products. In addition, using a non-uniform piecewise polynomial basis, we are able to achieve smaller approximation error than using bases adopted in previous PRT-based works, such as spherical harmonics and wavelets. Using hardware acceleration, we demonstrate that our system generates images comparable to [ [JMLH01] ]at real-time frame-rates.     

Caustic Forecasting: Unbiased Estimation of Caustic Lighting for Global Illumination

We present an unbiased method for generating caustic lighting using importance sampled Path Tracing with Caustic Forecasting. Our technique is part of a straightforward rendering scheme which extends the Illumination by Weak Singularities method to allow for fully unbiased global illumination with rapid convergence. A photon shooting preprocess, similar to that used in Photon Mapping, generates photons that interact with specular geometry. These photons are then clustered, effectively dividing the scene into regions which will contribute similar amounts of caustic lighting to the image. Finally, the photons are stored into spatial data structures associated with each cluster, and the clusters themselves are organized into a spatial data structure for fast searching. During rendering we use clusters to decide the caustic energy importance of a region, and use the local photons to aid in importance sampling, effectively reducing the number of samples required to capture caustic lighting.     

Multiple Axis‐Aligned Filters for Rendering of Combined Distribution Effects

Distribution effects such as diffuse global illumination, soft shadows and depth of field, are most accurately rendered using Monte Carlo ray or path tracing. However, physically accurate algorithms can take hours to converge to a noise‐free image. A recent body of work has begun to bridge this gap, showing that both individual and multiple effects can be achieved accurately and efficiently. These methods use sparse sampling, GPU raytracers, and adaptive filtering for reconstruction. They are based on a Fourier analysis, which models distribution effects as a wedge in the frequency domain. The wedge can be approximated as a single large axis‐aligned filter, which is fast but retains a large area outside the wedge, and therefore requires a higher sampling rate; or a tighter sheared filter, which is slow to compute. The state‐of‐the‐art fast sheared filtering method combines low sampling rate and efficient filtering, but has been demonstrated for individual distribution effects only, and is limited by high‐dimensional data storage and processing. We present a novel filter for efficient rendering of combined effects, involving soft shadows and depth of field, with global (diffuse indirect) illumination. We approximate the wedge spectrum with multiple axis‐aligned filters, marrying the speed of axis‐aligned filtering with an even more accurate (compact and tighter) representation than sheared filtering. We demonstrate rendering of single effects at comparable sampling and frame‐rates to fast sheared filtering. Our main practical contribution is in rendering multiple distribution effects, which have not even been demonstrated accurately with sheared filtering. For this case, we present an average speedup of 6× compared with previous axis‐aligned filtering methods.     

Efficient Rendering of Local Subsurface Scattering

A novel approach is presented to efficiently render local subsurface scattering effects. We introduce an importance sampling scheme for a practical subsurface scattering model. It leads to a simple and efficient rendering algorithm, which operates in image space, and which is even amenable for implementation on graphics hardware. We demonstrate the applicability of our technique to the problem of skin rendering, for which the subsurface transport of light typically remains local. Our implementation shows that plausible images can be rendered interactively using hardware acceleration.     

A General BRDF Representation Based on Tensor Decomposition

Generating photo‐realistic images through Monte Carlo rendering requires efficient representation of light–surface interaction and techniques for importance sampling. Various models with good representation abilities have been developed but only a few of them have their importance sampling procedure. In this paper, we propose a method which provides a good bidirectional reflectance distribution function (BRDF) representation and efficient importance sampling procedure. Our method is based on representing BRDF as a function of tensor products. Four‐dimensional measured BRDF tensor data are factorized using Tucker decomposition. A large data set is used for comparing the proposed BRDF model with a number of well‐known BRDF models. It is shown that the underlying model provides good approximation to BRDFs.     

Bidirectional Importance Sampling for Unstructured Direct Illumination

Recent research in bidirectional importance sampling has focused primarily on structured illumination sources such as distant environment maps, while unstructured illumination has received little attention. In this paper, we present a method for bidirectional importance sampling of unstructured illumination, allowing us to use the same method for sampling both distant as well as local/indirect sources. Building upon recent work in [ WFA*05 ], we model complex illumination as a large set of point lights. The subsequent sampling process draws samples only from this point set. We start by constructing a piecewise constant approximation for the lighting using an illumination cut [ CPWAP08 ]. We show that this cut can be used directly for illumination importance sampling. We then use BRDF importance sampling followed by sample counting to update the cut, resulting in a bidirectional distribution that closely approximates the product of the illumination and BRDF. Drawing visibility samples from this new distribution significantly reduces the sampling variance. As a main advance over previous work, our method allows for unstructured sources, including arbitrary local direct lighting and one-bounce of indirect lighting.     

Accurate Translucent Material Rendering under Spherical Gaussian Lights

In this paper we present a new algorithm for accurate rendering of translucent materials under Spherical Gaussian (SG) lights. Our algorithm builds upon the quantized‐diffusion BSSRDF model recently introduced in [ [dI11] ]. Our main contribution is an efficient algorithm for computing the integral of the BSSRDF with an SG light. We incorporate both single and multiple scattering components. Our model improves upon previous work by accounting for the incident angle of each individual SG light. This leads to more accurate rendering results, notably elliptical profiles from oblique illumination. In contrast, most existing models only consider the total irradiance received from all lights, hence can only generate circular profiles. Experimental results show that our method is suitable for rendering of translucent materials under finite‐area lights or environment lights that can be approximated by a small number of SGs.     

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.     

Sample‐Based Manifold Filtering for Interactive Global Illumination and Depth of Field

We present a fast reconstruction filtering method for images generated with Monte Carlo–based rendering techniques. Our approach specializes in reducing global illumination noise in the presence of depth‐of‐field effects at very low sampling rates and interactive frame rates. We employ edge‐aware filtering in the sample space to locally improve outgoing radiance of each sample. The improved samples are then distributed in the image plane using a fast, linear manifold‐based approach supporting very large circles of confusion. We evaluate our filter by applying it to several images containing noise caused by Monte Carlo–simulated global illumination, area light sources and depth of field. We show that our filter can efficiently denoise such images at interactive frame rates on current GPUs and with as few as 4–16 samples per pixel. Our method operates only on the colour and geometric sample information output of the initial rendering process. It does not make any assumptions on the underlying rendering technique and sampling strategy and can therefore be implemented completely as a post‐process filter.     

A Multidirectional Occlusion Shading Model for Direct Volume Rendering

In this paper, we present a novel technique which simulates directional light scattering for more realistic interactive visualization of volume data. Our method extends the recent directional occlusion shading model by enabling light source positioning with practically no performance penalty. Light transport is approximated using a tilted cone‐shaped function which leaves elliptic footprints in the opacity buffer during slice‐based volume rendering. We perform an incremental blurring operation on the opacity buffer for each slice in front‐to‐back order. This buffer is then used to define the degree of occlusion for the subsequent slice. Our method is capable of generating high‐quality soft shadowing effects, allows interactive modification of all illumination and rendering parameters, and requires no pre‐computation.     

Portal‐Masked Environment Map Sampling

We present a technique to efficiently importance sample distant, all‐frequency illumination in indoor scenes. Standard environment sampling is inefficient in such cases since the distant lighting is typically only visible through small openings (e.g. windows). This visibility is often addressed by manually placing a portal around each window to direct samples towards the openings; however, uniformly sampling the portal (its area or solid angle) disregards the possibly high frequency environment map. We propose a new portal importance sampling technique which takes into account both the environment map and its visibility through the portal, drawing samples proportional to the product of the two. To make this practical, we propose a novel, portal‐rectified reparametrization of the environment map with the key property that the visible region induced by a rectangular portal projects to an axis‐aligned rectangle. This allows us to sample according to the desired product distribution at an arbitrary shading location using a single (precomputed) summed‐area table per portal. Our technique is unbiased, relevant to many renderers, and can also be applied to rectangular light sources with directional emission profiles, enabling efficient rendering of non‐diffuse light sources with soft shadows.     

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.     

Compression and Importance Sampling of Near‐Field Light Sources

This paper presents a method for compressing measured datasets of the near‐field emission of physical light sources (represented by raysets). We create a mesh on the bounding surface of the light source that stores illumination information. The mesh is augmented with information about directional distribution and energy density. We have developed a new approach to smoothly generate random samples on the illumination distribution represented by the mesh, and to efficiently handle importance sampling of points and directions. We will show that our representation can compress a 10 million particle rayset into a mesh of a few hundred triangles. We also show that the error of this representation is low, even for very close objects.     

IlluminationCut

We present a novel algorithm, IlluminationCut, for rendering images using the many‐lights framework. It handles any light source that can be approximated with virtual point lights (VPLs) as well as highly glossy materials. The algorithm extends the Multidimensional Lightcuts technique by effectively creating an illumination‐aware clustering of the product‐space of the set of points to be shaded and the set of VPLs. Additionally, the number of visibility queries for each product‐space cluster is reduced by using an adaptive sampling technique. Our framework is flexible and achieves around 3 – 6 times speedup over previous state‐of‐the‐art methods.     

Exploiting Visibility Correlation in Direct Illumination

The visibility function in direct illumination describes the binary visibility over a light source, e.g., an environment map. Intuitively, the visibility is often strongly correlated between nearby locations in time and space, but exploiting this correlation without introducing noticeable errors is a hard problem. In this paper, we first study the statistical characteristics of the visibility function. Then, we propose a robust and unbiased method for using estimated visibility information to improve the quality of Monte Carlo evaluation of direct illumination. Our method is based on the theory of control variates, and it can be used on top of existing state‐of‐the‐art schemes for importance sampling. The visibility estimation is obtained by sparsely sampling and caching the 4D visibility field in a compact bitwise representation. In addition to Monte Carlo rendering, the stored visibility information can be used in a number of other applications, for example, ambient occlusion and lighting design.     

Spatio‐Temporal Filtering of Indirect Lighting for Interactive Global Illumination

We introduce a screen‐space statistical filtering method for real‐time rendering with global illumination. It is inspired by statistical filtering proposed by Meyer et al. to reduce the noise in global illumination over a period of time by estimating the principal components from all rendered frames. Our work extends their method to achieve nearly real‐time performance on modern GPUs. More specifically, our method employs the candid covariance‐free incremental PCA to overcome several limitations of the original algorithm by Meyer et al., such as its high computational cost and memory usage that hinders its implementation on GPUs. By combining the reprojection and per‐pixel weighting techniques, our method handles the view changes and object movement in dynamic scenes as well.     

Pre‐computed Gathering of Multi‐Bounce Glossy Reflections

Recent work in interactive global illumination addresses diffuse and moderately glossy indirect lighting effects, but high‐frequency effects such as multi‐bounce reflections on highly glossy surfaces are often ignored. Accurately simulating such effects is important to convey the realistic appearance of materials such as chrome and shiny metal. In this paper, we present an efficient method for visualizing multi‐bounce glossy reflections at interactive rates under environment lighting. Our main contribution is a pre‐computation–based method which efficiently gathers subsequent highly glossy reflection passes modelled with a non‐linear transfer function representation based on the von Mises–Fisher distribution. We show that our gathering method is superior to scattered sampling. To exploit the sparsity of the pre‐computed data, we apply perfect spatial hashing. As a result, we are able to visualize multi‐bounce glossy reflections at interactive rates at a low pre‐computation cost.     

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.     

Parallel Multiple‐Bounce Irradiance Caching

Building designers rely on predictive rendering techniques to design naturally and artificially lit environments. However, despite decades of work on the correctness of global illumination rendering techniques, our ability to accurately predict light levels in buildings—and to do so in a short time frame as part of an iterative design process—remains limited. In this paper, we present a novel approach to parallelizing construction of an irradiance cache over multiple‐bounce paths. Relevant points for irradiance calculation based on one or multiple cameras are located by tracing rays through multiple‐bounce paths. Irradiance values are then saved to a cache in reverse bounce order so that the irradiance calculation at each bounce samples from previously calculated values. We show by comparison to high‐dynamic range photography of a moderately complex space that our method can predict luminance distribution as accurately as Radiance , the most widely validated tool used today for architectural predictive rendering of daylit spaces, and that it is faster by an order of magnitude.     

Real‐time Shading with Filtered Importance Sampling

We propose an analysis of numerical integration based on sampling theory, whereby the integration error caused by aliasing is suppressed by pre‐filtering. We derive a pre‐filter for evaluating the illumination integral yielding filtered importance sampling, a simple GPU‐based rendering algorithm for image‐based lighting. Furthermore, we extend the algorithm with real‐time visibility computation. Free from any pre‐computation, the algorithm supports fully dynamic scenes and, above all, is simple to implement.