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.     

Volumetric Vector-Based Representation for Indirect Illumination Caching

This paper introduces a caching technique based on a volumetric representation that captures low-frequency indirect illumination. This structure is intended for efficient storage and manipulation of illumination. It is based on a 3D grid that stores a fixed set of irradiance vectors. During preprocessing, this representation can be built using almost any existing global illumination software. During rendering, the indirect illumination within a voxel is interpolated from its associated irradiance vectors, and is used as additional local light sources. Compared with other techniques, the 3D vector-based representation of our technique offers increased robustness against local geometric variations of a scene. We thus demonstrate that it may be employed as an efficient and high-quality caching data structure for bidirectional rendering techniques such as particle tracing or photon mapping.     

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.     

Rendering Caustics on Non-Lambertian Surfaces

This paper presents a new technique for rendering caustics on non-Lambertian surfaces. The method is based on an extension of the photon map which removes previous restrictions limiting the usage to Lambertian surfaces. We add information about the incoming direction to the photons and this allows us to combine the photon map with arbitrary reflectance functions. By using a cone-filter we improve the quality of the radiance estimate in particular at discontinuities. Furthermore we introduce balancing of the photon map which not only reduces the memory requirements but also significantly reduces the rendering time. We have used the method to render caustics on surfaces with reflectance functions varying from Lambertian to glossy specular.     

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.     

基于光子映射的辐照度缓存算法

提出了一种全局光照计算方法,结合了两个知名的技术,光子映射和辐照度缓存.光子映射具有视点无关的优势,辐照度缓存可以快速计算间接光照,但后者是视点相关的,为了使光照缓存记录覆盖整个场景,辐照度缓存算法需要手动设置很多相机.利用这两种技术的各自优势,通过光子图来计算改进后的视点无关的辐照度缓存算法,实现了快速而准确的全局光...     

Reducing photon-mapping bandwidth by query reordering

Photon mapping places an enormous burden on the memory hierarchy. Rendering a 512 x 512 image of a simple scene can require more than 196 Gbytes of raw bandwidth to the photon map data structure. This bandwidth is a major obstacle to real time photon mapping. This paper investigates two approaches for reducing the required bandwidth: 1) reordering the kNN searches and 2) cache conscious data structures. Using a Hilbert curve reordering, we demonstrate an experimental lower bound of 15 Mbytes of bandwidth for the same scene. Unfortunately, this improvement of four orders of magnitude requires a prohibitive amount of intermediate storage. We introduce two novel cost-effective algorithms that reduce the bandwidth by one order of magnitude. Scenes of different complexities are shown to exhibit similar reductions in bandwidth. We explain why the choice of data structure does not achieve similar reductions. We also examine the interaction of query reordering with two photon map acceleration techniques, importance sampling and the irradiance cache. Query reordering exploits the additional coherence that arises from the use of importance sampling in scenes with glossy surfaces. Irradiance caching also benefits from query reordering, even when complex surface geometry reduces the effectiveness of the irradiance cache.     

Shape from Texture without Boundaries

We describe a shape from texture method that constructs an estimate of surface geometry using only the deformation of individual texture elements. Our method does not need to use either the boundary of the observed surface or any assumption about the overall distribution of elements.The method assumes that surface texture elements are drawn from a number of different types, each of fixed shape. Neither the shape of the elements nor the number of types need be known in advance. We show that, with this assumption and assuming a generic, scaled orthographic view and texture, each type of texture element can be reconstructed in a frontal coordinate system from image instances. Interest-point methods supply a method of simultaneously obtaining instances of each texture element automatically and defining each type of element. Furthermore, image instances that have been marked in error can be identified and ignored using the Expectation-Maximization algorithm. A further EM procedure yields a surface reconstruction and a relative irradiance map from the data. We provide numerous examples of reconstructions for images of real scenes, show a comparison between our reconstruction and range maps, and demonstrate that the reconstructions display geometric and irradiance phenomena that can be observed in the original image. First online version published in February, 2006     

Stylized Caustics: Progressive Rendering of Animated Caustics

In recent years, much work was devoted to the design of light editing methods such as relighting and light path editing. So far, little work addressed the target‐based manipulation and animation of caustics, for instance to a differently‐shaped caustic, text or an image. The aim of this work is the animation of caustics by blending towards a given target irradiance distribution. This enables an artist to coherently change appearance and style of caustics, e.g., for marketing applications and visual effects. Generating a smooth animation is nontrivial, as photon density and caustic structure may change significantly. Our method is based on the efficient solution of a discrete assignment problem that incorporates constraints appropriate to make intermediate blends plausibly resemble caustics. The algorithm generates temporally coherent results that are rendered with stochastic progressive photon mapping. We demonstrate our system in a number of scenes and show blends as well as a key frame animation.     

Grouped photon mapping

This paper proposes a novel architecture called Grouped Photon Mapping, which combines standard photon mapping with the light-beam concept to improve the nearest-neighbor density estimation method. Based on spatial coherence, we cluster all of photons, which are deposited in the photon map, into different beam-like groups. Each group of photons is individually stored in an isolated photon map. By the distribution of the photons in each photon map, we construct a polygonal boundary to represent a beam-like illuminated area. These boundaries offer a more accurate and flexible sampling area to filter neighbor photons around the query point. In addition, by a level of detail technique, we can control the photon-count in each group to obtain a balance between biases and noise. The results of our experiments prove that our method can successfully reduce bias errors and light leakage. Especially, for complicated caustic effects through a gemstone-like object, we can render a smoother result than standard photon mapping.     

Interactive Global Photon Mapping

We present a photon mapping technique capable of computing high quality global illumination at interactive frame rates. By extending the concept of photon differentials to efficiently handle diffuse reflections, we generate footprints at all photon hit points. These enable illumination reconstruction by density estimation with variable kernel bandwidths without having to locate the k nearest photon hits first. Adapting an efficient BVH construction process for ray tracing acceleration, we build photon maps that enable the fast retrieval of all hits relevant to a shading point. We present a heuristic that automatically tunes the BVH build's termination criterion to the scene and illumination conditions. As all stages of the algorithm are highly parallelizable, we demonstrate an implementation using NVidia's CUDA manycore architecture running at interactive rates on a single GPU. Both light source and camera may be freely moved with global illumination fully recalculated in each frame.     

The Beam Radiance Estimate for Volumetric Photon Mapping

We present a new method for efficiently simulating the scattering of light within participating media. Using a theoretical reformulation of volumetric photon mapping, we develop a novel photon gathering technique for participating media. Traditional volumetric photon mapping samples the in‐scattered radiance at numerous points along the length of a single ray by performing costly range queries within the photon map. Our technique replaces these multiple point‐queries with a single beam‐query, which explicitly gathers all photons along the length of an entire ray. These photons are used to estimate the accumulated in‐scattered radiance arriving from a particular direction and need to be gathered only once per ray. Our method handles both fixed and adaptive kernels, is faster than regular volumetric photon mapping, and produces images with less noise.     

Irradiance regression for efficient final gathering in global illumination

Photon mapping is widely used for global illumination rendering because of its high computational efficiency. But its efficiency is still limited, mainly by the intensive sampling required in final gathering, a process that is critical for removing low frequency artifacts of density estimation. In this paper, we propose a method to predict the final gathering estimation with direct density estimation, thereby achieving high quality global illumination by photon mapping with high efficiency. We first sample the irradiance of a subset of shading points by both final gathering and direct radiance estimation. Then we use the samples as a training set to predict the final gathered irradiance of other shading points through regression. Consequently, we are able to achieve about three times overall speedup compared with straightforward final gathering in global illumination computation with the same rendering quality.     

Visualization of cosmological particle-based datasets

We describe our visualization process for a particle-based simulation of the formation of the first stars and their impact on cosmic history. The dataset consists of several hundred time-steps of point simulation data, with each time-step containing approximately two million point particles. For each time-step, we interpolate the point data onto a regular grid using a method taken from the radiance estimate of photon mapping. We import the resulting regular grid representation into ParaView, with which we extract isosurfaces across multiple variables. Our images provide insights into the evolution of the early universe, tracing the cosmic transition from an initially homogeneous state to one of increasing complexity. Specifically, our visualizations capture the build-up of regions of ionized gas around the first stars, their evolution, and their complex interactions with the surrounding matter. These observations will guide the upcoming James Webb Space Telescope, the key astronomy mission of the next decade.     

Estimating Photometric Properties from Image Collections

We address the problem of jointly estimating the scene illumination, the radiometric camera calibration and the reflectance properties of an object using a set of images from a community photo collection. The highly ill-posed nature of this problem is circumvented by using appropriate representations of illumination, an empirical model for the nonlinear function that relates image irradiance with intensity values and additional assumptions on the surface reflectance properties. Using a 3D model recovered from an unstructured set of images, we estimate the coefficients that represent the illumination for each image using a frequency framework. For each image, we also compute the corresponding camera response function. Additionally, we calculate a simple model for the reflectance properties of the 3D model. A robust non-linear optimization is proposed exploiting the high sparsity present in the problem.     

Single-pass Scalable Subsurface Rendering with Lightcuts

This paper presents a new, scalable, single pass algorithm for computing subsurface scattering using the diffusion approximation. Instead of pre‐computing a globally conservative estimate of the surface irradiance like previous two pass methods, the algorithm simultaneously refines hierarchical and adaptive estimates of both the surface irradiance and the subsurface transport. By using an adaptive, top‐down refinement method, the algorithm directs computational effort only to simulating those eye‐surface‐light paths that make significant contributions to the final image. Because the algorithm is driven by image importance, it scales more efficiently than previous methods that have a linear dependence on translucent surface area. We demonstrate that in scenes with many translucent objects and in complex lighting environments, our new algorithm has a significant performance advantage.     

Photon Differential Splatting for Rendering Caustics

We present a photon splatting technique which reduces noise and blur in the rendering of caustics. Blurring of illumination edges is an inherent problem in photon splatting, as each photon is unaware of its neighbours when being splatted. This means that the splat size is usually based on heuristics rather than knowledge of the local flux density. We use photon differentials to determine the size and shape of the splats such that we achieve adaptive anisotropic flux density estimation in photon splatting. As compared to previous work that uses photon differentials, we present the first method where no photons or beams or differentials need to be stored in a map. We also present improvements in the theory of photon differentials, which give more accurate results and a faster implementation. Our technique has good potential for GPU acceleration, and we limit the number of parameters requiring user adjustment to an overall smoothing parameter and the number of photons to be traced.     

Photon recollision probability in discrete crown canopies

The photon recollision probability in vegetation canopies, defined as the probability that a photon, after having interacted with a canopy element, will interact again, is a useful tool in remote sensing and ecological applications, enabling to link canopy optical properties at different wavelength and to estimate radiation absorption. In this work, a method is presented to estimate the photon recollision probability for horizontally homogeneous leaf canopies with arbitrary leaf angle distribution as well as for discrete crown canopies. The estimation is based on analytical approximation of the first-order recollision probability. Using the analytical solution of the two-stream equations of radiative transfer and Monte Carlo modeling, the first-order photon recollision probability is shown to slightly underestimate the mean recollision probability. Also, an approximation formula for the mean recollision probability in a horizontally homogeneous canopy is presented as a function of leaf area index. The method to calculate photon recollision probability in discrete crown canopies requires only the knowledge of total and between-crown canopy transmittance and is thus independent of the geometric-optical model used.     

Into the Blue: Better Caustics through Photon Relaxation

The photon mapping method is one of the most popular algorithms employed in computer graphics today. However, obtaining good results is dependent on several variables including kernel shape and bandwidth, as well as the properties of the initial photon distribution. While the photon density estimation problem has been the target of extensive research, most algorithms focus on new methods of optimising the kernel to minimise noise and bias. In this paper we break from convention and propose a new approach that directly redistributes the underlying photons. We show that by relaxing the initial distribution into one with a blue noise spectral signature we can dramatically reduce background noise, particularly in areas of uniform illumination. In addition, we propose an efficient heuristic to detect and preserve features and discontinuities. We then go on to demonstrate how reconfiguration also permits the use of very low bandwidth kernels, greatly improving render times whilst reducing bias.     

重要度驱动的自适应Projection Map在光子图中的应用

在全局光照算法中,光子图算法是一种与视点无关的物空间辐射度近似计算方法,提出了一种基于重要度驱动采样的自适应Projection map算法,利用它可以在光子图算法中提高光子发射的有效性和准确性,加快渲染速度并取得更好的图像质量.实验表明,该算法能够有效地减少光源发射光子的次数,提高光子的命中率,具有相当的应用价值.