Rendering photorealistic images is a costly process which can take up to several days in the case of high quality images. In most cases, the task of sampling the incident radiance function to evaluate the illumination integral is responsible for an important share of the computation time. Therefore, to reach acceptable rendering times, the illumination integral must be evaluated using a limited set of samples. Such a restriction raises the question of how to obtain the most accurate approximation possible with such a limited set of samples. One must thus ensure that sampling produces the highest amount of information possible by carefully placing and weighting the limited set of samples. Furthermore, the integral evaluation should take into account not only the information brought by sampling but also possible information available prior to sampling, such as the integrand smoothness. This idea of sparse information and the need to fully exploit the little information available is present throughout this book. The presented methods correspond to the state-of-the-art solutions in computer graphics, and take into account information which had so far been underexploited (or even neglected) by the previous approaches. The intended audiences are Ph.D. students and researchers in the field of realistic image synthesis or global illumination algorithms, or any person with a solid background in graphics and numerical techniques.

Autorentext

Ricardo Marques received his Master's degree in Computer Graphics and Distributed Parallel Computation from Universidade do Minho (Fall 2009), after which he worked as a researcher in the same university. He joined INRIA and the FRVSense team as a PhD student in Fall 2010 under the supervision of Kadi Bouatouch. His thesis work has focused on spherical integration methods applied to light transport simulation. He defended his PhD thesis in Fall 2013 and joined the Mimetric INRIA research team as a research engineer in 2014. Christian Bouville is presently an invited researcher in the FRVSense team at IRISA in Rennes, France. He was a team leader, project leader, and Emeritus expert at Orange Labs until 2006 and has been involved in many European and national projects. His main fields of research are now global illumination models and image-based rendering with a special interest in machine learning approaches. Luis Paulo Santos in an Assistant Professor at the Universidade do Minho, Portugal. He published several papers on both computer graphics and parallel processing on international conferences and journals. He managed two nationally funded graphics R&D projects and participates in multiple European projects with both academia and industry. His main research interests lie on Interactive Global Illumination and Parallel Processing. He has been a member of the Direction Board of the Portuguese chapter of Eurographics since 2008, was Deputy Director of the University of Minho's Department of Informations from 2010-2012, and Director of the Doctoral Program on Informatics over the same period. He also acts as Associated Editor of Elsevier's Computers & Graphics journal. Kadi Bouatouch was an electronics and automatic systems engineer (ENSEM 1974). He was awarded a PhD in 1977 and a higher doctorate in computer science in the field of computer graphics in 1989. He is working on global illumination, lighting simulation for complex environments, GPU-base rendering, andcomputer vision. He is currently a Professor at the University of Rennes 1 (France) and a researcher at IRISA. He is a member of Eurographics.

Inhalt
Introduction.- Spherical Fibonacci Point Sets for QMC Estimates of Illumination Integrals.- Bayesian Monte Carlo for Global Illumination.- Bibliography.- Authors' Biographies.