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.     

Anomalous Dispersion in Predictive Rendering

In coloured media, the index of refraction does not decrease monotonically with increasing wavelength, but behaves in a quite non-monotonical way. This behaviour is called anomalous dispersion and results from the fact that the absorption of a material influences its index of refraction.
So far, this interesting fact has not been widely acknowledged by the graphics community. In this paper, we demonstrate how to calculate the correct refractive index for a material based on its absorption spectrum with the Kramers-Kronig relation, and we discuss for which types of objects this effect is relevant in practice.     

Diorama Construction From a Single Image

Diorama artists produce a spectacular 3D effect in a confined space by generating depth illusions that are faithful to the ordering of the objects in a large real or imaginary scene. Indeed, cognitive scientists have discovered that depth perception is mostly affected by depth order and precedence among objects. Motivated by these findings, we employ ordinal cues to construct a model from a single image that similarly to Dioramas, intensifies the depth perception. We demonstrate that such models are sufficient for the creation of realistic 3D visual experiences. The initial step of our technique extracts several relative depth cues that are well known to exist in the human visual system. Next, we integrate the resulting cues to create a coherent surface. We introduce wide slits in the surface, thus generalizing the concept of cardboard cutout layers. Lastly, the surface geometry and texture are extended alongside the slits, to allow small changes in the viewpoint which enriches the depth illusion.     

Depth-of-Field Rendering by Pyramidal Image Processing

We present an image-based algorithm for interactive rendering depth-of-field effects in images with depth maps. While previously published methods for interactive depth-of-field rendering suffer from various rendering artifacts such as color bleeding and sharpened or darkened silhouettes, our algorithm achieves a significantly improved image quality by employing recently proposed GPU-based pyramid methods for image blurring and pixel disocclusion. Due to the same reason, our algorithm offers an interactive rendering performance on modern GPUs and is suitable for real-time rendering for small circles of confusion. We validate the image quality provided by our algorithm by side-by-side comparisons with results obtained by distributed ray tracing.     

Automatic Conversion of Mesh Animations into Skeleton-based Animations

Recently, it has become increasingly popular to represent animations not by means of a classical skeleton‐based model, but in the form of deforming mesh sequences. The reason for this new trend is that novel mesh deformation methods as well as new surface based scene capture techniques offer a great level of flexibility during animation creation. Unfortunately, the resulting scene representation is less compact than skeletal ones and there is not yet a rich toolbox available which enables easy post‐processing and modification of mesh animations. To bridge this gap between the mesh‐based and the skeletal paradigm, we propose a new method that automatically extracts a plausible kinematic skeleton, skeletal motion parameters, as well as surface skinning weights from arbitrary mesh animations. By this means, deforming mesh sequences can be fully‐automatically transformed into fullyrigged virtual subjects. The original input can then be quickly rendered based on the new compact bone and skin representation, and it can be easily modified using the full repertoire of already existing animation tools.     

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.     

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.     

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.     

Energy Aware Color Sets

We present a design technique for colors with the purpose of lowering the energy consumption of the display device. Our approach is based on a screen space variant energy model. The result of our design is a set of distinguishable iso-lightness colors guided by perceptual principles. We present two variations of our approach. One is based on a set of discrete user-named (categorical) colors, which are analyzed according to their energy consumption. The second is based on the constrained continuous optimization of color energy in the perceptually uniform CIELAB color space. We quantitatively compare our two approaches with a traditional choice of colors, demonstrating that we typically save approximately 40 percent of the energy. The color sets are applied to examples from the 2D visualization of nominal data and volume rendering of 3D scalar fields.     

Cutting and Pasting Irregularly Shaped Patches for Texture Synthesis

This paper proposes a patch‐based texture synthesis approach that cuts and stitches irregularly shaped texture patches to generate new texture images with minimized visual discontinuity. It works well on a wide range of textures. A semiautomatic algorithm is developed to obtain the irregularly shaped patches. To synthesize strictly structured textures, a regular pasting method is proposed to identify the texture structures and subsequently position the irregularly shaped patches according to the identified structures. The results and comparisons with related work are given.     

Efficient and Accurate Rendering of Complex Light Sources

We present a new method for estimating the radiance function of complex area light sources. The method is based on Jensen's photon mapping algorithm. In order to capture high angular frequencies in the radiance function, we incorporate the angular domain into the density estimation. However, density estimation in position-direction space makes it necessary to find a tradeoff between the spatial and angular accuracy of the estimation. We identify the parameters which are important for this tradeoff and investigate the typical estimation errors. We show how the large data size, which is inherent to the underlying problem, can be handled. The method is applied to different automotive tail lights. It can be applied to a wide range of other real-world light sources.     

Single Photo Estimation of Hair Appearance

Significant progress has been made in high-quality hair rendering, but it remains difficult to choose parameter values that reproduce a given real hair appearance. In particular, for applications such as games where naive users want to create their own avatars, tuning complex parameters is not practical. Our approach analyses a single flash photograph and estimates model parameters that reproduce the visual likeness of the observed hair. The estimated parameters include color absorptions, three reflectance lobe parameters of a multiple-scattering rendering model, and a geometric noise parameter. We use a novel melanin-based model to capture the natural subspace of hair absorption parameters. At its core, the method assumes that images of hair with similar color distributions are also similar in appearance. This allows us to recast the issue as an image retrieval problem where the photo is matched with a dataset of rendered images; we thus also match the model parameters used to generate these images. An earth-mover's distance is used between luminance-weighted color distributions to gauge similarity. We conduct a perceptual experiment to evaluate this metric in the context of hair appearance and demonstrate the method on 64 photographs, showing that it can achieve a visual likeness for a large variety of input photos.     

Estimating Specular Roughness and Anisotropy from Second Order Spherical Gradient Illumination

This paper presents a novel method for estimating specular roughness and tangent vectors, per surface point, from polarized second order spherical gradient illumination patterns. We demonstrate that for isotropic BRDFs, only three second order spherical gradients are sufficient to robustly estimate spatially varying specular roughness. For anisotropic BRDFs, an additional two measurements yield specular roughness and tangent vectors per surface point. We verify our approach with different illumination configurations which project both discrete and continuous fields of gradient illumination. Our technique provides a direct estimate of the per-pixel specular roughness and thus does not require off-line numerical optimization that is typical for the measure-and-fit approach to classical BRDF modeling.     

Enclosing Surfaces for Point Clusters Using 3D Discrete Voronoi Diagrams

Point clusters occur in both spatial and non-spatial data. In the former context they may represent segmented particle data, in the latter context they may represent clusters in scatterplots. In order to visualize such point clusters, enclosing surfaces lead to much better comprehension than pure point renderings.
We propose a flexible system for the generation of enclosing surfaces for 3D point clusters. We developed a GPU-based 3D discrete Voronoi diagram computation that supports all surface extractions. Our system provides three different types of enclosing surfaces. By generating a discrete distance field to the point cluster and extracting an isosurface from the field, an enclosing surface with any distance to the point cluster can be generated. As a second type of enclosing surfaces, a hull of the point cluster is extracted. The generation of the hull uses a projection of the discrete Voronoi diagram of the point cluster to an isosurface to generate a polygonal surface. Generated hulls of non-convex clusters are also non-convex. The third type of enclosing surfaces can be created by computing a distance field to the hull and extracting an isosurface from the distance field. This method exhibits reduced bumpiness and can extract surfaces arbitrarily close to the point cluster without losing connectedness.
We apply our methods to the visualization of multidimensional spatial and non-spatial data. Multidimensional clusters are extracted and projected into a 3D visual space, where the point clusters are visualized. The respective clusters can also be visualized in object space when dealing with multidimensional particle data.