🚀 go-pugleaf

...is not a faculty candidate talk, but should be very interesting
nonetheless, particularly if you're interested in vision, the new CAVE
system, VR/CHI, etc.  Please note that we have been moved to ECCR
**245** for the rest of the semester.

There are two open slots on Shree's schedule for thursday (11:30 and
1:30) if you're interested in speaking with him.

UNCONVENTIONAL VISION SENSORS

Shree Nayar 
Chair, Department of Computer Science
Columbia University

2/22/2001
3:30pm-4:30pm
ECCR 245

What can be perceived by a human or computed by a machine from an
image is fundamentally restricted by the captured data. Current
imaging systems are severely limited in spatial resolution, field of
view, and dynamic range. In this talk, we present new vision sensors
that provide unconventional forms of visual information.  The first
part of the talk focuses on the use of catadioptrics (lenses and
mirrors) for capturing unusually large fields of view. We describe
several methods for obtaining single viewpoint and multi-viewpoint
images. The second part of the talk addresses the problem of acquiring
high dynamic range images using a low dynamic range detector. We
present two approaches for extracting the desired extra bits at each
pixel; the first one uses multiple images while the second uses just a
single image.  Several interactive demonstrations of our results will
be shown. These results have implications for digital photography,
immersive imaging, image based rendering, 3D scene modeling, and
advanced interfaces.

Shree K. Nayar is a Professor in the Department of Computer Science at
Columbia University. He received his Ph.D.  degree in Electrical and
Computer Engineering from the Robotics Institute at Carnegie Mellon
University in 1990. He currently heads the Columbia Automated Vision
Environment (CAVE), which is dedicated to the development of advanced
computer vision systems. His research is focused on three areas,
namely, the creation of novel vision sensors, the design of physics
based models for vision, and the development of algorithms for scene
understanding. His work is motivated by applications in the fields of
digital imaging, computer graphics, human-machine interfaces,
robotics, and image understanding. He has received the David Marr
Price twice (1990 and 1995), the David and Lucile Packard Fellowship
(1992), the National Young Investigator Award (1993) and the Keck
Foundation Award for Excellence in Teaching (1995).