ColloquiaTalk by Michael Burl on Wednesday, May 2

[Margery Ishmael]

Wednesday, May 2 in Ryerson 251 at 2:30 p.m.

Michael Burl, Machine Learning Systems Group at the Jet Propulsion 
Laboratory, California

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Title:     Mining Large Image Collections

Abstract:
      Improvements in acquisition and storage technology have led to an
explosion in the number and size of image collections in a variety of
fields from medical imaging to the petroleum industry to digital
libraries and the Internet to space exploration. Within these datasets
there is a potential wealth of information; however, transforming from
the raw data (perhaps millions of images each containing millions of
pixels) to a higher-level understanding of the content of an image
collection is a difficult task both due to the size of the datasets and
the difficulty of automatically interpreting image data. Recent attempts
to approach the problem using a distributed set of human labelers
[ClickWorkers] are interesting, but ultimately do not provide a
long-term, reusable solution. In contrast, maturing technologies in data
mining, computer vision, and machine learning, coupled with rapidly
improving and affordable parallel and distributed hardware, have the
potential to solve current and future image mining problems in an
efficient, scalable way.
      In this talk, we will provide an overview of our work toward
systems and algorithms that can extract semantically meaningful content
from data, with emphasis on specific algorithms that have been developed
for visual recognition, querying, and discovery. We will also describe
an exciting new project, the Autonomous Sciencecraft Constellation
(ASC), that involves integrating perception, planning, and execution
capabilities to create a highly capable spacecraft constellation that
can make onboard decisions and carry out actions based on the content of
the data collected.

Bio:
      Michael C. Burl received the Ph.D. degree in Electrical Engineering
from the California Institute of Technology in 1997 with a dissertation
entitled "Recognition of Visual Object Classes". He is currently a
Technical Group Leader and Senior Staff Member in the Machine Learning
Systems Group at the Jet Propulsion Laboratory. He is the inventor of
Diamond Eye, a distributed architecture for large-scale image mining and
he also developed the core algorithms in JARtool, a tool for
automatically cataloging volcanoes in the Magellan SAR imagery of Venus.
He previously worked in  the Battlefield Surveillance Group at MIT
Lincoln Laboratory, where he developed algorithms for the detection and
classification of tactical and strategic ground targets in
high-resolution polarimetric SAR imagery. He is an organizer of the
Third (and Fourth) Workshops on Mining Scientific Data Sets and has been
a program committee member and invited speaker at various data mining
and knowledge discovery conferences.
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*The talk will be followed by refreshments in Ryerson 255*
(If you would like to meet the speaker, please send e-mail to 
marge at cs.uchicago.edu)

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-- 
Margery Ishmael
Department of Computer Science
The University of Chicago
1100 E. 58th Street
Chicago, IL. 60637

Tel. 773-834-8977  Fax. 773-702-8487