We present radiance regression functions for fast rendering of global illumination in scenes with dynamic local light sources. A radiance regression function (RRF) represents a non-linear mapping from local and contextual attributes of surface points, such as position, viewing direction, and lighting condition, to their indirect illumination values. The RRF is obtained from precomputed shading samples through regression analysis, which determines a function that best fits the shading data. For a given scene, the shading samples are precomputed by an offline renderer. The key idea behind our approach is to exploit the nonlinear coherence of the indirect illumination data to make the RRF both compact and fast to evaluate. We model the RRF as a multilayer acyclic feed-forward neural network, which provides a close functional approximation of the indirect illumination and can be efficiently evaluated at run time. To effectively model scenes with spatially variant material properties, we utilize an augmented set of attributes as input to the neural network RRF to reduce the amount of inference that the network needs to perform. To handle scenes with greater geometric complexity, we partition the input space of the RRF model and represent the subspaces with separate, smaller RRFs that can be evaluated more rapidly. As a result, the RRF model scales well to increasingly complex scene geometry and material variation. Because of its compactness and ease of evaluation, the RRF model enables real-time rendering with full global illumination effects, including changing caustics and multiple-bounce high-frequency glossy interreflections.

We present the first parallel surface reconstruction algorithm that runs entirely on the GPU. Like existing implicit surface reconstruction methods, our algorithm first builds an octree for the given set of oriented points, then computes an implicit function over the space of the octree, and finally extracts an isosurface as a watertight triangle mesh. A key component of our algorithm is a novel technique for octree construction on the GPU. This technique builds octrees in real time and uses level-order traversals to exploit the fine-grained parallelism of the GPU. Moreover, the technique produces octrees that provide fast access to the neighborhood information of each octree node, which is critical for fast GPU surface reconstruction. With an octree so constructed, our GPU algorithm performs Poisson surface reconstruction, which produces high-quality surfaces through a global optimization. Given a set of 500 K points, our algorithm runs at the rate of about five frames per second, which is over two orders of magnitude faster than previous CPU algorithms. To demonstrate the potential of our algorithm, we propose a user-guided surface reconstruction technique which reduces the topological ambiguity and improves reconstruction results for imperfect scan data. We also show how to use our algorithm to perform on-the-fly conversion from dynamic point clouds to surfaces as well as to reconstruct fluid surfaces for real-time fluid simulation.

We describe a technique for real-time rendering of dynamic, spatially-varying BRDFs in static scenes with all-frequency shadows from environmental and point lights. The 6D SVBRDF is represented with a general microfacet model and spherical lobes fit to its 4D spatially-varying normal distribution function (SVNDF). A sum of spherical Gaussians (SGs) provides an accurate approximation with a small number of lobes. Parametric BRDFs are fit on-the-fly using simple analytic expressions; measured BRDFs are fit as a preprocess using nonlinear optimization. Our BRDF representation is compact, allows detailed textures, is closed under products and rotations, and supports reflectance of arbitrarily high specularity. At run-time, SGs representing the NDF are warped to align the half-angle vector to the lighting direction and multiplied by the microfacet shadowing and Fresnel factors. This yields the relevant 2D view slice on-the-fly at each pixel, still represented in the SG basis. We account for macro-scale shadowing using a new, nonlinear visibility representation based on spherical signed distance functions (SSDFs). SSDFs allow per-pixel interpolation of high-frequency visibility without ghosting and can be multiplied by the BRDF and lighting efficiently on the GPU.

We present RenderAnts, the first system that enables interactive Reyes rendering on GPUs. Taking RenderMan scenes and shaders as input, our system first compiles RenderMan shaders to GPU shaders. Then all stages of the basic Reyes pipeline, including bounding/splitting, dicing, shading, sampling, compositing and filtering, are executed on GPUs using carefully designed data-parallel algorithms. Advanced effects such as shadows, motion blur and depth-of-field can also be rendered. In order to avoid exhausting GPU memory, we introduce a novel dynamic scheduling algorithm to bound the memory consumption during rendering. The algorithm automatically adjusts the amount of data being processed in parallel at each stage so that all data can be maintained in the available GPU memory. This allows our system to maximize the parallelism in all individual stages of the pipeline and achieve superior performance. We also propose a multi-GPU scheduling technique based on work stealing so that the system can support scalable rendering on multiple GPUs. The scheduler is designed to minimize inter-GPU communication and balance workloads among GPUs. We demonstrate the potential of RenderAnts using several complex RenderMan scenes and an open source movie entitled Elephants Dream. Compared to Pixar's PRMan, our system can generate images of comparably high quality, but is over one order of magnitude faster. For moderately complex scenes, the system allows the user to change the viewpoint, lights and materials while producing photorealistic results at interactive speed.

We describe a new, analytic approximation to the airlight integral from scattering media whose density is modeled as a sum of Gaussians. The approximation supports real-time rendering of inhomogeneous media including their shadowing and scattering effects. For each Gaussian, this approximation samples the scattering integrand at the projection of its center along the view ray but models attenuation and shadowing with respect to the other Gaussians by integrating density along the fixed path from light source to 3D center to view point. Our method handles isotropic, single-scattering media illuminated by point light sources or low-frequency lighting environments. We also generalize models for reflectance of surfaces from constant-density to inhomogeneous media, using simple optical depth averaging in the direction of the light source or all around the receiver point. Our real-time renderer is incorporated into a system for real-time design and preview of realistic animated fog, steam, or smoke.