Frequency-Based Kernel Estimation for Progressive Photon Mapping

PosterInternational audienceWe present an extension to Hachisuka et al.'s Progressive Photon Mapping (or PPM) algorithm [Hachisuka et al. 2008] in which we estimate the radius of the density estimation kernels using frequency analysis of light transport [Durand et al. 2005]. We predict the local radiance frequency at the surface of objects using a Gaussian approximation, and use it to drive the size of the density estimation kernels, in order to accelerate convergence. The key is to add frequency information to a small proportion of photons: frequency photons. In addition to contributing to the density estimation, they will provide frequency information