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.     

Gradient‐based Interpolation and Sampling for Real‐time Rendering of Inhomogeneous,Single‐scattering Media

We present a real‐time rendering algorithm for inhomogeneous, single scattering media, where all‐frequency shading effects such as glows, light shafts, and volumetric shadows can all be captured. The algorithm first computes source radiance at a small number of sample points in the medium, then interpolates these values at other points in the volume using a gradient‐based scheme that is efficiently applied by sample splatting. The sample points are dynamically determined based on a recursive sample splitting procedure that adapts the number and locations of sample points for accurate and efficient reproduction of shading variations in the medium. The entire pipeline can be easily implemented on the GPU to achieve real‐time performance for dynamic lighting and scenes. Rendering results of our method are shown to be comparable to those from ray tracing.     

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.     

A Robust Illumination Estimate for Chromatic Adaptation in Rendered Images

We propose a method that improves automatic colour correction operations for rendered images. In particular, we propose a robust technique for estimating the visible and pertinent illumination in a given scene. We do this at very low computational cost by mostly re-using information that is already being computed during the image synthesis process. Conventional illuminant estimations either operate only on 2D image data, or, if they do go beyond pure image analysis, only use information on the luminaires found in the scene. The latter is usually done with little or no regard for how the light sources actually affect the part of the scene that is being viewed. Our technique goes beyond that, and also takes object reflectance into account, as well as the incident light that is actually responsible for the colour of the objects that one sees. It is therefore able to cope with difficult cases, such as scenes with mixed illuminants, complex scenes with many light sources of varying colour, or strongly coloured indirect illumination.     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

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.     

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.     

Spectralization: Reconstructing spectra from sparse data

Traditional RGB reflectance and light data suffers from the problem of metamerism and is not suitable for rendering purposes where exact color reproduction under many different lighting conditions is needed. Nowadays many setups for cheap and fast acquisition of RGB or similar trichromatic datasets are available. In contrast to this, multi‐ or even hyper‐spectral measurements require costly hardware and have severe limitations in many cases. In this paper, we present an approach to combine efficiently captured RGB data with spectral data that can be captured with small additional effort for example by scanning a single line of an image using a spectral line‐scanner. Our algorithm can infer spectral reflectances and illumination from such sparse spectral and dense RGB data. Unlike other approaches, our method reaches acceptable perceptual errors with only three channels for the dense data and thus enables further use of highly efficient RGB capture systems. This way, we are able to provide an easier and cheaper way to capture spectral textures, BRDFs and environment maps for the use in spectral rendering systems.     

Product Importance Sampling for Light Transport Path Guiding

The efficiency of Monte Carlo algorithms for light transport simulation is directly related to their ability to importance‐sample the product of the illumination and reflectance in the rendering equation. Since the optimal sampling strategy would require knowledge about the transport solution itself, importance sampling most often follows only one of the known factors – BRDF or an approximation of the incident illumination. To address this issue, we propose to represent the illumination and the reflectance factors by the Gaussian mixture model (GMM), which we fit by using a combination of weighted expectation maximization and non‐linear optimization methods. The GMM representation then allows us to obtain the resulting product distribution for importance sampling on‐the‐fly at each scene point. For its efficient evaluation and sampling we preform an up‐front adaptive decimation of both factor mixtures. In comparison to state‐of‐the‐art sampling methods, we show that our product importance sampling can lead to significantly better convergence in scenes with complex illumination and reflectance.     

Reconstructing 3D Shape,Albedo and Illumination from a Single Face Image

The morphable model has been employed to efficiently describe 3D face shape and the associated albedo with a reduced set of basis vectors. The spherical harmonics (SH) model provides a compact basis to well approximate the image appearance of a Lambertian object under different illumination conditions. Recently, the SH and morphable models have been integrated for 3D face shape reconstruction. However, the reconstructed 3D shape is either inconsistent with the SH bases or obtained just from landmarks only. In this work, we propose a geometrically consistent algorithm to reconstruct the 3D face shape and the associated albedo from a single face image iteratively by combining the morphable model and the SH model. The reconstructed 3D face geometry can uniquely determine the SH bases, therefore the optimal 3D face model can be obtained by minimizing the error between the input face image and a linear combination of the associated SH bases. In this way, we are able to preserve the consistency between the 3D geometry and the SH model, thus refining the 3D shape reconstruction recursively. Furthermore, we present a novel approach to recover the illumination condition from the estimated weighting vector for the SH bases in a constrained optimization formulation independent of the 3D geometry. Experimental results show the effectiveness and accuracy of the proposed face reconstruction and illumination estimation algorithm under different face poses and multiple‐light‐source illumination conditions.     

Light montage for perceptual image enhancement

Recent photography techniques such as sculpting with light show great potential in compositing beautiful images from fixed‐viewpoint photos under multiple illuminations. The process relies heavily on the artists’ experience and skills using the available tools. An apparent trend in recent works is to facilitate the interaction making it less time‐consuming and addressable not only to experts, but also novices. We propose a method that automatically creates enhanced light montages that are comparable to those produced by artists. It detects and emphasizes cues that are important for perception by introducing a technique to extract depth and shape edges from an unconstrained light stack. Studies show that these cues are associated with silhouettes and suggestive contours which artists use to sketch and construct the layout of paintings. Textures, due to perspective distortion, offer essential cues that depict shape and surface slant. We balance the emphasis between depth edges and reflectance textures to enhance the sense of both shape and reflectance properties. Our light montage technique works perfectly with a few to hundreds of illuminations for each scene. Experiments show great results for static scenes making it practical for small objects, interiors and small‐scale outdoor scenes. Dynamic scenes may be captured using spatially distributed light setups such as light domes. The approach could also be applied to time‐lapse photos, with the sun as the main light source.     

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.     

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.     

Superresolution Reflectance Fields: Synthesizing images for intermediate light directions

Captured reflectance fields tend to provide a relatively coarse sampling of the incident light directions. As a result, sharp illumination features, such as highlights or shadow boundaries, are poorly reconstructed during relighting; highlights are disconnected, and shadows show banding artefacts. In this paper, we propose a novel interpolation technique for 4D reflectance fields that reconstructs plausible images even for non-observed light directions. Given a sparsely sampled reflectance field, we can effectively synthesize images as they would have been obtained from denser sampling. The processing pipeline consists of three steps: (1) segmentation of regions where intermediate lighting cannot be obtained by blending, (2) appropriate flow algorithms for highlights and shadows, plus (3) a final reconstruction technique that uses image-based priors to faithfully correct errors that might be introduced by the segmentation or flow step. The algorithm reliably reproduces scenes that contain specular highlights, interreflections, shadows or caustics.     

Instant Caching for Interactive Global Illumination

The ability to interactively render dynamic scenes with global illumination is one of the main challenges in computer graphics. The improvement in performance of interactive ray tracing brought about by significant advances in hardware and careful exploitation of coherence has rendered the potential of interactive global illumination a reality. However, the simulation of complex light transport phenomena, such as diffuse interreflections, is still quite costly to compute in real time. In this paper we present a caching scheme, termed Instant Caching, based on a combination of irradiance caching and instant radiosity. By reutilising calculations from neighbouring computations this results in a speedup over previous instant radiosity‐based approaches. Additionally, temporal coherence is exploited by identifying which computations have been invalidated due to geometric transformations and updating only those paths. The exploitation of spatial and temporal coherence allows us to achieve superior frame rates for interactive global illumination within dynamic scenes, without any precomputation or quality loss when compared to previous methods; handling of lighting and material changes are also demonstrated.     

Floating Textures

We present a novel multi‐view, projective texture mapping technique. While previous multi‐view texturing approaches lead to blurring and ghosting artefacts if 3D geometry and/or camera calibration are imprecise, we propose a texturing algorithm that warps (“floats”) projected textures during run‐time to preserve crisp, detailed texture appearance. Our GPU implementation achieves interactive to real‐time frame rates. The method is very generally applicable and can be used in combination with many image‐based rendering methods or projective texturing applications. By using Floating Textures in conjunction with, e.g., visual hull rendering, light field rendering, or free‐viewpoint video, improved rendering results are obtained from fewer input images, less accurately calibrated cameras, and coarser 3D geometry proxies.     

Stereo Light Probe

In this paper we present a practical, simple and robust method to acquire the spatially‐varying illumination of a real‐world scene. The basic idea of the proposed method is to acquire the radiance distribution of the scene using high‐dynamic range images of two reflective balls. The use of two light probes instead of a single one allows to estimate, not only the direction and intensity of the light sources, but also the actual position in space of the light sources. To robustly achieve this goal we first rectify the two input spherical images, then, using a region‐based stereo matching algorithm, we establish correspondences and compute the position of each light. The radiance distribution so obtained can be used for augmented reality applications, photo‐realistic rendering and accurate reflectance properties estimation. The accuracy and the effectiveness of the method have been tested by measuring the computed light position and rendering synthetic version of a real object in the same scene. The comparison with standard method that uses a simple spherical lighting environment is also shown.     

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.     

Turning a Digital Camera into an Absolute 2D Tele‐Colorimeter

We present a simple and effective technique for absolute colorimetric camera characterization, invariant to changes in exposure/aperture and scene irradiance, suitable in a wide range of applications including image‐based reflectance measurements, spectral pre‐filtering and spectral upsampling for rendering, to improve colour accuracy in high dynamic range imaging. Our method requires a limited number of acquisitions, an off‐the‐shelf target and a commonly available projector, used as a controllable light source, other than the reflected radiance to be known. The characterized camera can be effectively used as a 2D tele‐colorimeter, providing the user with an accurate estimate of the distribution of luminance and chromaticity in a scene, without requiring explicit knowledge of the incident lighting power spectra. We validate the approach by comparing our estimated absolute tristimulus values (XYZ data in ) with the measurements of a professional 2D tele‐colorimeter, for a set of scenes with complex geometry, spatially varying reflectance and light sources with very different spectral power distribution.     

Panorama light‐field imaging

We present a novel approach to recording and computing panorama light fields. In contrast to previous methods that estimate panorama light fields from focal stacks or naive multi‐perspective image stitching, our approach is the first that processes ray entries directly and does not require depth reconstruction or matching of image features. Arbitrarily complex scenes can therefore be captured while preserving correct occlusion boundaries, anisotropic reflections, refractions, and other light effects that go beyond diffuse reflections of Lambertian surfaces.