Performance and quality analysis of convolution-based volume illumination

Convolution-based techniques for volume rendering are among the fastest in the on-the-fly volumetric illumination category. Such methods, however, are still considerably slower than conventional local illumination techniques. In this paper we describe how to adapt two commonly used strategies for reducing aliasing artifacts, namely pre-integration and supersampling, to such techniques. These strategies can help reduce the sampling rate of the lighting information (thus the number of convolutions), bringing considerable performance benefits. We present a comparative analysis of their effectiveness in offering performance improvements. We also analyze the (negligible) differences they introduce when comparing their output to the reference method. These strategies can be highly beneficial in setups where direct volume rendering of continuously streaming data is desired and continuous recomputation of full lighting information is too expensive, or where memory constraints make it preferable not to keep additional precomputed volumetric data in memory. In such situations these strategies make single pass, convolution-based volumetric illumination models viable for a broader range of applications, and this paper provides practical guidelines for using and tuning such strategies to specific use cases

Doctor of Philosophy

dissertationReal-time global illumination is the next frontier in real-time rendering. In an attempt to generate realistic images, games have followed the film industry into physically based shading and will soon begin integrating global illumination techniques. Traditional methods require too much memory and too much time to compute for real-time use. With Modular and Delta Radiance Transfer we precompute a scene-independent, low-frequency basis that allows us to calculate complex indirect lighting calculations in a much lower dimensional subspace with a reduced memory footprint and real-time execution. The results are then applied as a light map on many different scenes. To improve the low frequency results, we also introduce a novel screen space ambient occlusion technique that allows us to generate a smoother result with fewer samples. These three techniques, low and high frequency used together, provide a viable indirect lighting solution that can be run in milliseconds on today's hardware, providing a useful new technique for indirect lighting in real-time graphics

Fast Rendering of Forest Ecosystems with Dynamic Global Illumination

Real-time rendering of large-scale, forest ecosystems remains a challenging problem, in that important global illumination effects, such as leaf transparency and inter-object light scattering, are difficult to capture, given tight timing constraints and scenes that typically contain hundreds of millions of primitives. We propose a new lighting model, adapted from a model previously used to light convective clouds and other participating media, together with GPU ray tracing, in order to achieve these global illumination effects while maintaining near real-time performance. The lighting model is based on a lattice-Boltzmann method in which reflectance, transmittance, and absorption parameters are taken from measurements of real plants. The lighting model is solved as a preprocessing step, requires only seconds on a single GPU, and allows dynamic lighting changes at run-time. The ray tracing engine, which runs on one or multiple GPUs, combines multiple acceleration structures to achieve near real-time performance for large, complex scenes. Both the preprocessing step and the ray tracing engine make extensive use of NVIDIA\u27s Compute Unified Device Architecture (CUDA)

Neural Free-Viewpoint Relighting for Glossy Indirect Illumination

Precomputed Radiance Transfer (PRT) remains an attractive solution for real-time rendering of complex light transport effects such as glossy global illumination. After precomputation, we can relight the scene with new environment maps while changing viewpoint in real-time. However, practical PRT methods are usually limited to low-frequency spherical harmonic lighting. All-frequency techniques using wavelets are promising but have so far had little practical impact. The curse of dimensionality and much higher data requirements have typically limited them to relighting with fixed view or only direct lighting with triple product integrals. In this paper, we demonstrate a hybrid neural-wavelet PRT solution to high-frequency indirect illumination, including glossy reflection, for relighting with changing view. Specifically, we seek to represent the light transport function in the Haar wavelet basis. For global illumination, we learn the wavelet transport using a small multi-layer perceptron (MLP) applied to a feature field as a function of spatial location and wavelet index, with reflected direction and material parameters being other MLP inputs. We optimize/learn the feature field (compactly represented by a tensor decomposition) and MLP parameters from multiple images of the scene under different lighting and viewing conditions. We demonstrate real-time (512 x 512 at 24 FPS, 800 x 600 at 13 FPS) precomputed rendering of challenging scenes involving view-dependent reflections and even caustics.Comment: 13 pages, 9 figures, to appear in cgf proceedings of egsr 202

Image-based rendering and synthesis

Multiview imaging (MVI) is currently the focus of some research as it has a wide range of applications and opens up research in other topics and applications, including virtual view synthesis for three-dimensional (3D) television (3DTV) and entertainment. However, a large amount of storage is needed by multiview systems and are difficult to construct. The concept behind allowing 3D scenes and objects to be visualized in a realistic way without full 3D model reconstruction is image-based rendering (IBR). Using images as the primary substrate, IBR has many potential applications including for video games, virtual travel and others. The technique creates new views of scenes which are reconstructed from a collection of densely sampled images or videos. The IBR concept has different classification such as knowing 3D models and the lighting conditions and be rendered using conventional graphic techniques. Another is lightfield or lumigraph rendering which depends on dense sampling with no or very little geometry for rendering without recovering the exact 3D-models.published_or_final_versio