Konversatorium on Friday, November 23, 2018 - 10:30
Friday, November 23, 2018 - 10:30
Seminar room E186 (Favoritenstraße 9, Stiege 1, 5th floor)
Image-Space Metaballs using Deep Learning (DAAV)
Robert Horvath (Inst. 193-02 CG)
10 + 10
Metaballs are implicit surfaces that are used to model organic-looking shapes and fluids.
Accurate rendering of three-dimensional Metaballs is typically done using ray-casting, which is computationally expensive and not suitable for real-time applications, therefore different approximate methods for rendering Metaballs have been developed.
In this thesis, a new approach to rendering Metaballs efficiently and fast enough for real-time applications using Deep Learning is proposed.
A simplified representation of Metaballs is rendered to textures that are then fed to a neural network that outputs multiple depth, normal and base color buffers that are combined using deferred shading to produce an image that resembles the result of a renderer using ray-casting.
Vis 2018 Report
Haichao Miao (Inst. 193-02 CG)
20 + 10