View Item 
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        •   Utrecht University Student Theses Repository Home
        • UU Theses Repository
        • Theses
        • View Item
        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UU Student Theses RepositoryBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

        Q-Learned Importance Sampling for Physically Based Light Transport on the GPU

        Thumbnail
        View/Open
        q-learned-importance-final.pdf (67.61Mb)
        Publication date
        2018
        Author
        Mastrigt, K. van
        Metadata
        Show full item record
        Summary
        We present a GPU implementation of Dahm and Keller's Q-learning based importance sampling technique. The method requires a caching scheme to store the radiance distributions that are learned during path tracing. We tested the method on a photon map, a Poisson disk distribution and the Poisson disk distribution with a new addition called light occlusion. We found that the uniformly distributed points of the photon map produces the best results. The method itself was tested on four different scenes. We show that in an optimized GPU path tracer the method can have a positive influence on the performance, depending on the difficulty of the scene. In a comparison to a bidirectional path tracer we see that the method is able to outperform the bidirectional path tracer in a scene that is almost exclusively lit by indirect lighting. We conclude that it can be beneficial to implement the method in a GPU based path tracer.
        URI
        https://studenttheses.uu.nl/handle/20.500.12932/28882
        Collections
        • Theses
        Utrecht university logo