Adaptive sampling and Markov chain Monte Carlo methods in light transport simulation
Research project funded by the Czech Science Foundation (GA ČR).
An important problem in computer graphics is realistic image synthesis, with light transport simulation being its fundamental component. The objective of this project is to develop new methods that will be able to efficiently simulate light in a much wider range of environments than the existing ones. To this end, we propose novel research on adaptive sampling in Monte Carlo methods as well as the use of Markov chain Monte Carlo. The main novelty of our research is a rigorous statistical approach to exploiting different sources of information – often suffering from statistical error – in adaptive simulation. Apart from making a theoretical contribution, our project will benefit practical applications such as the film industry or architectural visualization.