Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
(CS 528)
Capturing Shape and Reflection from Images
Steve Seitz
Computer Science Department
University of Washington
Monday, March 1, 2004, 4:15PM
TCSeq 200
http://graphics.stanford.edu/ba-colloquium/
Abstract
Surfaces in the real world reflect light in interesting and complex ways. For
instance, wood looks the way it does (different from leather, skin, hair,
satin, etc.) because it reflects light in a characteristic way, as a function
of illumination, viewpoint, and surface-varying grain. While humans have no
problem interpreting images of scenes with widely varying material properties,
developing computational mechanisms for handling realistic materials is a wide
open problem in computer vision.
In this talk, I will address the problem of reconstructing 3D shape models of
scenes with very general reflectance properties from images. The resulting
algorithms operate on an extremely broad class of materials and objects,
ranging from wood, to oxidized metal, to brushed fur.
This is collaborative work with Dan Goldman, Adrien Treuille, Brian Curless,
and Aaron Hertzmann.
About the Speaker
Steve Seitz is an Associate Professor in the Department of Computer Science and
Engineering at the University of Washington. He received his B.A. in computer
science and mathematics at the University of California, Berkeley in 1991 and
his Ph.D. in computer sciences at the University of Wisconsin, Madison in
1997. Following his doctoral work, he spent one year visiting the Vision
Technology Group at Microsoft Research, and subsequently two years as an
Assistant Professor in the Robotics Institute at Carnegie Mellon University. He
joined the faculty at the University of Washington in 2000. He was twice
awarded the David Marr Prize for the best paper at the International Conference
of Computer Vision, and has received an NSF Career Award, an ONR Young
Investigator Award, and an Alfred P. Sloan Fellowshp.
Contact: bac-coordinators@cs.stanford.edu
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