MIT Department of Electrical Engineering & Computer Science
Computing Meaningful Representations of People-Oriented Data
Matthew Brand
MIT Media Lab
Thursday, April 3, 1997
3:00 PM (2:45 refreshments)
Edgerton Hall, Room 34-101
EECS Special Seminar
Abstract
Effective algorithms for interacting with people-oriented data (text,
video, speech, music, etc.) will ultimately be grounded in perceptual and
cognitive psychology, just as compression algorithms for these media have a
psychophysical basis. This reflects the simple fact that these media will
be organized and searched by meaning. To this end, I will present systems
that produce codings of video and text that are both efficient (in the
information-theoretic sense) and psychologically meaningful. These systems
are built around novel maximum-likelihood algorithms that leverage
psychological datasets into workable interpreters of human-generated
signals. In their raw form, the algorithms address general problems such
as modeling non-Markovian systems and finding structure in non-metric data.
Conjoined to psychological meta-data and/or trained, they can find themes
in text, extract action scripts from video, and recognize complex gestures.
Other applications include gene classification, network configuration,
lip-reading, and over-the-shoulder tutors - machines that watch you work
and unobtrusively augment your activity. I'll conclude by considering how
the meta-data itself may be acquired.
URL of this page:
http://www-eecs.mit.edu/AY96-97/events/32.html
Created: Mar 27, 1997
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Modified: Jun 24, 1997
This announcement is from the MIT EECS 1996-97 archive.
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