5D Covariance Tracing for Efficient Defocus and Motion Blur

The rendering of effects such as motion blur and depth-of-field requires costly 5D integrals. We dramatically accelerate their computation through adaptive sampling and reconstruction based on the prediction of the anisotropy and bandwidth of the integrand. For this, we develop a new frequency analysis of the 5D temporal light-field, and show that first-order motion can be handled through simple changes of coordinates in 5D. We further introduce a compact representation of the spectrum using the co- variance matrix and Gaussian approximations. We derive update equations for the 5 × 5 covariance matrices for each atomic light transport event, such as transport, occlusion, BRDF, texture, lens, and motion. The focus on atomic operations makes our work general, and removes the need for special-case formulas. We present a new rendering algorithm that computes 5D covariance matrices on the image plane by tracing paths through the scene, focusing on the single-bounce case. This allows us to reduce sampling rates when appropriate and perform reconstruction of images with complex depth-of-field and motion blur effects

Factored axis-aligned filtering for rendering multiple distribution effects

Monte Carlo (MC) ray-tracing for photo-realistic rendering often requires hours to render a single image due to the large sampling rates needed for convergence. Previous methods have attempted to filter sparsely sampled MC renders but these methods have high reconstruction overheads. Recent work has shown fast performance for individual effects, like soft shadows and indirect illumination, using axis-aligned filtering. While some components of light transport such as indirect or area illumination are smooth, they are often multiplied by high-frequency components such as texture, which prevents their sparse sampling and reconstruction. We propose an approach to adaptively sample and filter for simultaneously rendering primary (defocus blur) and secondary (soft shadows and indirect illumination) distribution effects, based on a multi-dimensional frequency analysis of the direct and indirect illumination light fields. We describe a novel approach of factoring texture and irradiance in the presence of defocus blur, which allows for pre-filtering noisy irradiance when the texture is not noisy. Our approach naturally allows for different sampling rates for primary and secondary effects, further reducing the overall ray count. While the theory considers only Lambertian surfaces, we obtain promising results for moderately glossy surfaces. We demonstrate 30x sampling rate reduction compared to equal quality noise-free MC. Combined with a GPU implementation and low filtering over-head, we can render scenes with complex geometry and diffuse and glossy BRDFs in a few seconds.National Science Foundation (U.S.) (Grant CGV 1115242)National Science Foundation (U.S.) (Grant CGV 1116303)Intel Corporation (Science and Technology Center for Visual Computing

Frequency Based Radiance Cache for Rendering Animations

International audienceWe propose a method to render animation sequences with direct distant lighting that only shades a fraction of the total pixels. We leverage frequency-based analyses of light transport to determine shading and image sampling rates across an animation using a samples cache. To do so, we derive frequency bandwidths that account for the complexity of distant lights, visibility, BRDF, and temporal coherence during animation. We finaly apply a cross-bilateral filter when rendering our final images from sparse sets of shading points placed according to our frequency-based oracles (generally < 25% of the pixels, per frame)

Foundations and Methods for GPU based Image Synthesis

Effects such as global illumination, caustics, defocus and motion blur are an integral part of generating images that are perceived as realistic pictures and cannot be distinguished from photographs. In general, two different approaches exist to render images: ray tracing and rasterization. Ray tracing is a widely used technique for production quality rendering of images. The image quality and physical correctness are more important than the time needed for rendering. Generating these effects is a very compute and memory intensive process and can take minutes to hours for a single camera shot. Rasterization on the other hand is used to render images if real-time constraints have to be met (e.g. computer games). Often specialized algorithms are used to approximate these complex effects to achieve plausible results while sacrificing image quality for performance. This thesis is split into two parts. In the first part we look at algorithms and load-balancing schemes for general purpose computing on graphics processing units (GPUs). Most of the ray tracing related algorithms (e.g. KD-tree construction or bidirectional path tracing) have unpredictable memory requirements. Dynamic memory allocation on GPUs suffers from global synchronization required to keep the state of current allocations. We present a method to reduce this overhead on massively parallel hardware architectures. In particular, we merge small parallel allocation requests from different threads that can occur while exploiting SIMD style parallelism. We speed-up the dynamic allocation using a set of constraints that can be applied to a large class of parallel algorithms. To achieve the image quality needed for feature films GPU-cluster are often used to cope with the amount of computation needed. We present a framework that employs a dynamic load balancing approach and applies fair scheduling to minimize the average execution time of spawned computational tasks. The load balancing capabilities are shown by handling irregular workloads: a bidirectional path tracer allowing renderings of complex effects at near interactive frame rates. In the second part of the thesis we try to reduce the image quality gap between production and real-time rendering. Therefore, an adaptive acceleration structure for screen-space ray tracing is presented that represents the scene geometry by planar approximations. The benefit is a fast method to skip empty space and compute exact intersection points based on the planar approximation. This technique allows simulating complex phenomena including depth-of-field rendering and ray traced reflections at real-time frame rates. To handle motion blur in combination with transparent objects we present a unified rendering approach that decouples space and time sampling. Thereby, we can achieve interactive frame rates by reusing fragments during the sampling step. The scene geometry that is potentially visible at any point in time for the duration of a frame is rendered in a rasterization step and stored in temporally varying fragments. We perform spatial sampling to determine all temporally varying fragments that intersect with a specific viewing ray at any point in time. Viewing rays can be sampled according to the lens uv-sampling to incorporate depth-of-field. In a final temporal sampling step, we evaluate the pre-determined viewing ray/fragment intersections for one or multiple points in time. This allows incorporating standard shading effects including and resulting in a physically plausible motion and defocus blur for transparent and opaque objects

A Local Frequency Analysis of Light Scattering and Absorption

(presented at SIGGRAPH 2014)International audienceRendering participating media requires significant computation, but the effect of volumetric scattering is often eventually smooth. This article proposes an innovative analysis of absorption and scattering of local light fields in the Fourier domain and derives the corresponding set of operators on the covariance matrix of the power spectrum of the light field. This analysis brings an efficient prediction tool for the behavior of light along a light path in participating media. We leverage this analysis to derive proper frequency prediction metrics in 3D by combining per-light path information in the volume.We demonstrate the use of these metrics to significantly improve the convergence of a variety of existing methods for the simulation of multiple scattering in participating media. First, we propose an efficient computation of second derivatives of the fluence, to be used in methods like irradiance caching. Second, we derive proper filters and adaptive sample densities for image-space adaptive sampling and reconstruction. Third, we propose an adaptive sampling for the integration of scattered illumination to the camera. Finally, we improve the convergence of progressive photon beams by predicting where the radius of light gathering can stop decreasing. Light paths in participating media can be very complex. Our key contribution is to show that analyzing local light fields in the Fourier domain reveals the consistency of illumination in such media and provides a set of simple and useful rules to be used to accelerate existing global illumination methods.Une nouvelle analyse locale de la diffusion et de l'absorption de la lumière dans l'espace de Fourier est combinée avec le tracé de covariance et permet une estimation rapide du contenu fréquentiel local; cette approche permet l'amélioration de nombreux algorithmes de rendu de milieux participants tels que Progressive Photon Beams et l'integration d'effets de diffusion simple et l'échantillonnage et la reconstruction d'effets de simple diffusion simple en espace image

A Frequency Analysis and Dual Hierarchy for Efficient Rendering of Subsurface Scattering

International audienceBSSRDFs are commonly used to model subsurface light transport in highly scattering media such as skin and marble. Rendering with BSSRDFs requires an additional spatial integration, which can be significantly more expensive than surface-only rendering with BRDFs. We introduce a novel hierarchical rendering method that can mitigate this additional spatial integration cost. Our method has two key components: a novel frequency analysis of subsurface light transport, and a dual hierarchy over shading and illumination samples. Our frequency analysis predicts the spatial and angular variation of outgoing radiance due to a BSSRDF. We use this analysis to drive adaptive spatial BSSRDF integration with sparse image and illumination samples. We propose the use of a dual-tree structure that allows us to simultaneously traverse a tree of shade points (i.e., pixels) and a tree of object-space illumination samples. Our dual-tree approach generalizes existing single-tree accelerations. Both our frequency analysis and the dual-tree structure are compatible with most existing BSSRDF models, and we show that our method improves rendering times compared to the state of the art method of Jensen and Buhler

Coded aperture and coded exposure photography : an investigation into applications and methods

This dissertation presents an introduction to the field of computational photography, and provides a survey of recent research. Specific attention is given to coded aperture and coded exposure theory and methods, as these form the basis for the experiments performed

Fast Computation of Single Scattering in Participating Media with Refractive Boundaries using Frequency Analysis

International audienceMany materials combine a refractive boundary and a participating media on the interior. If the material has a low opacity, single scattering effects dominate in its appearance. Refraction at the boundary concentrates the incoming light, resulting in an important phenomenon called volume caustics. This phenomenon is hard to simulate. Previous methods used point-based light transport, but attributed point samples inefficiently, resulting in long computation time. In this paper, we use frequency analysis of light transport to allocate point samples efficiently. Our method works in two steps: in the first step, we compute volume samples along with their covariance matrices, encoding the illumination frequency content in a compact way. In the rendering step, we use the covariance matrices to compute the kernel size for each volume sample: small kernel for high-frequency single scattering, large kernel for lower frequencies. Our algorithm computes volume caustics with fewer volume samples, with no loss of quality. Our method is both faster and uses less memory than the original method. It is roughly twice as fast and uses one fifth of the memory. The extra cost of computing covariance matrices for frequency information is negligible