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TUTORIAL I
Sunday June 15 Morning
FINDING PICTURES IN DIGITAL LIBRARIES
Prof. David Forsyth and Prof. Jitendra Malik, U.C. Berkeley
Very large collections of pictures are now common, and there is a
desperate need to be able to index them. Since users generally
want to find images depicting particular objects, the application
focuses attention on important research problems in computer
vision. Partial solutions to these problems lead to useful systems,
because often the only alternative is to index the
collection by hand.
TUTORIAL II
Sunday June 15 Afternoon
ROBUST TECHNIQUES FOR COMPUTER VISION
Prof. Peter Meer, Rutgers University
Robust estimation techniques have become standard
tools in computer vision. The tutorial discusses robust techniques
in the context of image understanding problems, and provides
practical suggestions for achieving the best possible results.
TUTORIAL III
Monday June 16 Morning
COMPUTATIONAL SENSORS FOR VISION
Dr. Vladimir Brajovic and Prof. Takeo Kanade, Carnegie Mellon University
Computational Sensors are chips which tightly integrate
sensing and processing. Successful sensors have been
demonstrated for computer vision applications and are
typical of the next generation of vision sensors.
The tutorial will review several representative examples of
computational sensors and will cover basic (primarily analog)
techniques for computation in VLSI.
TUTORIAL IV
Monday June 16 Afternoon
SYNTHETIC APERTURE RADAR (SAR) IMAGE UNDERSTANDING
Dr. Les Novak, Lincoln Laboratory, Massachussets Institute of Technology
This tutorial presents a basic understanding of synthetic
aperture radar imagery. Basic SAR image characteristics
will be defined and demonstrated using real and simulated
SAR. Basic techniques for SAR processing, filtering, and
object recognition will be described. Advanced SAR processing
techniques, such as superresolution, will also be addressed.