From Measurement to Fabrication: Data-Driven Representations of Material Appearance for Graphics and Vision
University of Virginia
Accurate models of the way materials scatter and absorb incident light are a
critical component in computer systems that synthesize realistic images of
virtual environments or infer properties of a 3D scene from natural images.
I will discuss emerging data-driven strategies along with my own research for
measuring and modeling the often complex optical properties of materials such
as brushed metal, cloth, wood, marble, and human skin. In particular, I will
highlight a system recently built at the University of Virginia that allows
accurately measuring the 3D shape and material properties of opaque objects.
I will also describe a recent project that demonstrates how to fabricate
physical replicas of complex spatially-varying materials using an off-the-shelf
Jason Lawrence received his PhD from
Princeton University and is currently an assistant professor in the Computer
Science Department at the University of Virginia. His research focuses on
efficient representations and measurement devices for material appearance,
real-time and physically-based rendering algorithms, and large-scale parallel
image processing. He is the recipient of an NSF CAREER award titled,
"The Inverse Shade Tree Framework for Material Acquisition, Analysis,
Hosted by Clayton Lewis.
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