Chris DeCoro will present his preFPO on Wednesday August 27 at 2PM in Room 402. The members of his committee are Szymon Rusinkiewicz (advisor); Tom Funkhouser and Tim Weyrich (readers); and Fei-Fei Li and Brian Kernighan (non-readers). A copy of his abstract follows below. Everyone is invited to attend his talk. =========================== Title: "Filters for Detail Control and Stylization in Rendering" This dissertation examines a new class of filtering operations that are applied during rendering -- the process of synthesizing an image from geometry. These ``rendering filters'' allow for detail control, creative stylization, and noise rejection in ways not possible with purely image- or geometry-space filters. In particular: the subtractive shadow filter enables flexible control of shadowing level-of-detail in a real-time animation, allowing designers to rapidly prototype changes to materials and geometry. In our system, direct illumination is always computed and preserved in full detail. In contrast, the degree to which the perceptual cues provided by shadowing are maintained is controlled by the user, as a tradeoff between accuracy and rendering speed. Additionally, the subtractive shadow filter is able to take advantage of the low-frequency content of shadows, relative to direct illumination, to improve perceptual quality relative to conventional shadow computation with a limited number of lights. The stylized illumination filter gives the digital artist creative control over the appearance of shadows and illumination, replicating many of the effects frequently employed by traditional artists; In particular, we give the user control over the key parameters of inflation, brightness, softness, and abstraction. Because the filter operates in real time, the artist may design the desired effect with interactive feedback. The path-density filter allows for rejection of statistical outliers in the computation of global illumination solutions, significantly decreasing noise and improving convergence. The key insight of the method is to leverage density-estimation techniques in a high-dimensional space representing scattering events along light paths; paths in low-density regions are considered outliers. Unlike existing methods, it does so in a way that is both robust to large-scale noise, while efficient on well-behaved distributions.