Yamaguchi, TomoyaYatagawa, TatsuyaMorishima, ShigeoFu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes2018-10-072018-10-072018978-3-03868-073-4https://doi.org/10.2312/pg.20181271https://diglib.eg.org:443/handle/10.2312/pg20181271This paper proposes efficient path sampling for re-rendering scenes after material editing. The proposed sampling method is based on Metropolis light transport (MLT) and distributes more path samples to pixels whose values have been changed significantly by editing. First, we calculate the difference between images before and after editing to estimate the changes in pixel values. In this step, we render the difference image directly rather than calculating the difference in the images by separately rendering the images before and after editing. Then, we sample more paths for pixels with larger difference values and render the scene after editing by reducing variances of Monte Carlo estimators using the control variates. Thus, we can obtain rendering results with a small amount of noise using only a small number of path samples. We examine the proposed sampling method with a range of scenes and demonstrate that it achieves lower estimation errors and variances over the state-of-the-art methods.Ray tracingMetropolis light transportMaterial editingCCS ConceptsComputing methodologiesRay tracingGraphics processorsEfficient Metropolis Path Sampling for Material Editing and Re-rendering10.2312/pg.2018127121-24