Signal-Theoretic Representations of Visual Appearance
Speaker: Ravi Ramamoorthi , Columbia University
Date: May 18 2005
Time: 2:45PM to 3:45PM
Location: G449 (Patil/Kiva)
Host: Fredo Durand, CSAIL
Contact: Greg Shakhnarovich, xx3-8170, gregory@csail
Relevant URL: ABSTRACT:
Many problems in computer graphics require compact and accurate
representations of the appearance of objects, and the mathematical
algorithms to manipulate them. For instance, high quality real-time
rendering needs models for appearance effects like natural
illumination from wide-area light sources such as skylight, realistic
material properties like velvet, satin, paints, or wood, and shading
effects like soft shadows. These effects are also important in many
computer vision problems like recognition and surface reconstruction.
In these problems, we must often deal with complex high-dimensional
spaces. For instance, for real-time relighting in computer graphics,
or for lighting-insensitive recognition in computer vision, we must
consider the space of images of an object under all possible lighting
conditions. Since the illumination can in principle come from
anywhere, the appearance manifold would seem to be
infinite-dimensional. However, one can find lower-dimensional and
more compact structures that lead to efficient algorithms.
In this talk, we discuss a signal-theoretic approach to representing
appearance, where the illumination and reflection function are signals
and filters, and we apply many signal-processing tools such as
convolution, wavelet-based representation and sparse data
interpolation. These representations and tools are applicable to a
variety of problems in computer graphics and vision. We will present
methods for interactive rendering with complex lighting, reflectance
and soft shadows, new techniques for acquiring spatially varying
reflectance from a sparse set of photographs in image-based rendering,
and applications to inverse problems in graphics and vision.
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