Ravi Ramamoorthi, University of California, Berkeley talks about Sampling and Reconstruction of High-Dimensional Visual Appearance".
Date: March 9, 2011
Time: 11:00 am
Location: A.V. Williams Building, Room 2120
Producing realistic images in computer graphics, or acquiring the visual properties of realistic scenes in computer vision, often involves sampling high-dimensional datasets. One example comes from real-time rendering techniques, that often use a precomputed light transport matrix that can range from 4D - 6D, measuring variation across the image, as well as the space of lighting and viewing directions. Similar problems arise in appearance acquisition for computer vision, where one seeks to acquire data-driven models of shape and spatially-varying reflectance of real materials. Even in offline rendering in graphics, one is sampling a high-dimensional space, involving the pixel area, time for motion blur and depth of field for lens effects. Imaging applications are in many cases analogous to rendering, involving a sampling of the light field, or even just time for videos.