Virtual light fields for global illumination in computer graphics

This thesis presents novel techniques for the generation and real-time rendering of globally illuminated environments with surfaces described by arbitrary materials. Real-time rendering of globally illuminated virtual environments has for a long time been an elusive goal. Many techniques have been developed which can compute still images with full global illumination and this is still an area of active flourishing research. Other techniques have only dealt with certain aspects of global illumination in order to speed up computation and thus rendering. These include radiosity, ray-tracing and hybrid methods. Radiosity due to its view independent nature can easily be rendered in real-time after pre-computing and storing the energy equilibrium. Ray-tracing however is view-dependent and requires substantial computational resources in order to run in real-time. Attempts at providing full global illumination at interactive rates include caching methods, fast rendering from photon maps, light fields, brute force ray-tracing and GPU accelerated methods. Currently, these methods either only apply to special cases, are incomplete exhibiting poor image quality and/or scale badly such that only modest scenes can be rendered in real-time with current hardware. The techniques developed in this thesis extend upon earlier research and provide a novel, comprehensive framework for storing global illumination in a data structure - the Virtual Light Field - that is suitable for real-time rendering. The techniques trade off rapid rendering for memory usage and precompute time. The main weaknesses of the VLF method are targeted in this thesis. It is the expensive pre-compute stage with best-case O(N^2) performance, where N is the number of faces, which make the light propagation unpractical for all but simple scenes. This is analysed and greatly superior alternatives are presented and evaluated in terms of efficiency and error. Several orders of magnitude improvement in computational efficiency is achieved over the original VLF method. A novel propagation algorithm running entirely on the Graphics Processing Unit (GPU) is presented. It is incremental in that it can resolve visibility along a set of parallel rays in O(N) time and can produce a virtual light field for a moderately complex scene (tens of thousands of faces), with complex illumination stored in millions of elements, in minutes and for simple scenes in seconds. It is approximate but gracefully converges to a correct solution; a linear increase in resolution results in a linear increase in computation time. Finally a GPU rendering technique is presented which can render from Virtual Light Fields at real-time frame rates in high resolution VR presentation devices such as the CAVETM

Fast Radiative-Transfer-Equation-Based Image Reconstruction Algorithms for Non-Contact Diffuse Optical Tomography Systems

It is well known that the radiative transfer equation (RTE) is the most accurate deterministic light propagation model employed in diffuse optical tomography (DOT). RTE-based algorithms provide more accurate tomographic results than codes that rely on the diffusion equation (DE), which is an approximation to the RTE, in scattering dominant media. However, RTE based DOT (RTE-DOT) has limited utility in practice due to its high computational cost and lack of support for general non-contact imaging systems. In this dissertation, I developed fast reconstruction algorithms for RTE-based DOT (RTE-DOT), which consists of three independent components: an efficient linear solver for forward problems, an improved optimization solver for inverse problem, and the first light propagation model in free space that fully considers the angular dependency, which can provide a suitable measurement operator for RTE-DOT. This algorithm is validated and evaluated with numerical experiments and clinical data. According to these studies, the novel reconstruction algorithm is up to 30 times faster than traditional reconstruction techniques, while achieving comparable reconstruction accuracy

Innovative boundary integral and hybrid methods for diffuse optical imaging

Diffuse Optical Imaging (DOI), the study of the propagation of Near Infra-Red (NIR) light in biological media, is an emerging method in medical imaging. Its state-of-the-art is non-invasive, versatile and reasonably inexpensive. In Diffuse Optical Tomography (DOT), the adaptation of numerical methods such as the Finite Element Method (FEM) and, more recently the Boundary Element Method (BEM), has allowed the treatment of complex problems, even for in vivo functional three-dimensional imaging. This work is the first attempt to combine these two methods in DOT. The BEM-FEM is designed to tackle layered turbid media problems. It focuses on the region of interest by restraining the reconstruction to it. All other regions are treated as piecewise-constant in a surface-integral approach. We validated the model in concentric spheres and found that it compared well with an analytical result. We then performed functional imaging of the neonate’s motor cortex in vivo, in a reconstruction restricted to the brain, both with FEM and BEM-FEM. Another use of the BEM in DOI is also outlined. NIR Spectroscopy (NIRS) devices are particularly used in brain monitoring and Diffuse Optical Cortical Mapping (DOCM). Unfortunately, they are very often accompanied by rudimentary analysis of the data and the 3D appreciation of the problem is missed. The BEM DOCM developed in the current work represents an improvement, especially since a topographical representation of a motor activation in the cortex is clearly reconstructed in vivo. In the interest of computational speed an acceleration technique for the BEM has been developed. The Fast Multipole Method (FMM), which is based on the decomposition of Green’s function on a basis of Bessel and Hankel functions, eases the evaluation of the BEM matrix, along with a faster calculation of the solutions

ECOS 2012

The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology