Global illumination rendering via indirect light field regression

Global illumination is important and hard to render in computer graphics. We propose a novel technique to generate high quality global illumination images using regression analysis. Our algorithm has two stages. During sampling stage, we get the indirect light field and use it to train an artificial neural network model. In reconstruction stage, the neural network model is used to synthesize the final image. The experiments show our algorithm generates higher quality images than the previous methods.