Beckman Institute and Department of Computer Science
University of Illinois at Urbana-Champaign
Geometry and 3D computer vision: What we (kind of) know how to do,
what we don't, and why anyone should care
I will present my views on the role of geometry in computer vision, a
domain concerned with the automated interpretation of digital imagery.
I will focus on two challenging problems, namely the acquisition of
three-dimensional (3D) object and scene models from multiple pictures
--- a process known as 3D photography, and the
dentification of previously observed objects (or object categories) in new images --- a process known
as object recognition. In the first part of the talk, I will show that an essential
part of the relationship between the shape of solids bounded by smooth surfaces
and their image outlines is inherently projective. This observation leads to
a better qualitative understanding of the image formation process, as well as
effective image-based algorithms for high-fidelity 3D photography. In the second
part of my presentation, I will argue that object recognition is probably
the most challenging and exciting problem in computer vision today, but that,
despite exciting recent progress, several key representational issues (including,
but not limited to, geometric ones) have yet to be addressed. I will illustrate
this point by discussing some recent results and open issues. I will conclude
with a discussion of potential applications of 3D photography and object
recognition to non-traditional domains such as archaeology, anthropology, cultural
heritage preservation, film post-production and special effects, and forensics.
Joint work with Yasutaka Furukawa, Akash Kushal, Svetlana Lazebnik, Kenton McHenry,
Fred Rothganger, and Cordelia Schmid.
Friday, October 20, 2006
Biotechnology Auditorium - 1:30 p.m. to 2:30 p.m.