Department of Computer Science Colloquium

Tuesday February 26th, 2002 4:15pm

Upson Hall B17

A Signal-Processing Framework for Forward and
Inverse Rendering

**Ravir Ramamoorthi**

Stanford University Graphics

http://graphics.stanford.edu/~ravir/

Understanding
the nature of reflection and illumination is important in
many areas of computer graphics and computer vision.
In this talk, I describe a new way of looking at reflection on a curved
surface, as a special type of convolution of the incident
illumination and the reflective properties of the surface (technically, the
bi-directional reflectance distribution function or BRDF).
We formalize these notions by deriving a convolution theorem in terms of
the spherical harmonic coefficients of the lighting and
BRDF. This allows us to introduce a
signal-processing framework for reflection, wherein the incident lighting
is the signal, the BRDF is the filter, and the reflected light is obtained by
filtering the input illumination (signal) using the frequency response of the
BRDF filter.

I
will demonstrate applications in two areas.
First, we show how our
framework can be used for computing and displaying
synthetic images in real-time with natural illumination and physically-based
BRDFs. We will
call this the "forward rendering" or the convolution problem.
Next, we extend and apply our framework to estimating realistic lighting
and reflective properties from photographs, and show how this approach can be
used to synthesize very realistic images under novel lighting and viewing
conditions. We will call this the
"inverse rendering" or the deconvolution
problem. In my talk, I will first
describe the theoretical framework, and then discuss the above two applications.