OMPUTERS are becoming
sophisticated enough to identify people by the patterns of their
voices, fingerprints and irises, but they cannot yet distinguish
individuals by the subtle quirks in the way they move.
That may change, though. Many researchers are working on ways to
make computer programs better at spotting tiny expressive qualities
in gait and gesture.
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Automatic recognition of these fine gradations in movement could
lead to a host of uses, from improved security programs and earlier
diagnosis of movement disorders to more lifelike computer
animation.
At New York University, Christoph Breg- ler, an assistant
professor of computer science at the Courant Institute of
Mathematics, and two colleagues have received a National Science
Foundation grant to train computers to recognize the subtle
movements people make.
Dr. Bregler's approach combines the latest high-speed video
technology with the principles of a Slovak dance theorist who
flourished long before the age of computers.
For the technology in his project, he has equipped his university
laboratory with a dance floor and 10 high-resolution infrared
cameras that can run at up to 1,000 frames a second. He records
movement using a technique - one more familiar on a "Star Wars''
back lot than at the Courant Institute - called motion capture.
Motion capture is a workhorse for animated films, video games and
special effects. In one version of the technology, high-speed
infrared cameras track the position of reflective markers pasted to
bodysuits worn by performers. This information becomes the basis for
an animated or computer-generated version of the same movement.
The technology has limits, but Dr. Breg- ler, who has
collaborated with movie studios, hopes to extend them. "Right now,
the technology misses many ephemeral aspects of shape change," he
said, qualities that artists must often painstakingly add. "Motion
capture doesn't get at the individual expressiveness of how each
person moves. The best animation is still handcrafted by
animators."
To add this missing ingredient to motion capture, Dr. Bregler has
turned to the work of Rudolf von Laban, a dancer and choreographer
born in 1879. Among his many innovations, Laban created a notation
system known as Laban Movement Analysis to characterize fine shades
of movements. Now, based on work with dancers and experts in Laban
analysis in his lab, Dr. Breg- ler is assembling a databank of
motions, translating them into mathematics and writing programs so
that computers can recognize them.
Edward Warburton, the director of the dance education program at
N.Y.U., and Peggy Hockney, an expert in Laban Movement Analysis, are
the other principal investigators on the National Science Foundation
project. Dr. Warburton said Laban analysis was well suited to
refining the broad strokes of motion capture.
"Laban is concerned not just with the obvious stuff of where
people are, but with the nuances of how they got there," he said.
Laban's system addresses the difference, for instance, between
waving cheerfully or sadly, or the many differences in touch. "There
is the gentleness of touching someone as though your hands were
feathers," Dr. Warburton said, as well as a touch strong enough to
push a car.
Human experts will be needed to categorize these subtleties of
motion, but not for long, Dr. Bregler said. "In the beginning, we
need people to do the identifying," he said. "But then the computer
should be able to find these movements automatically."
He wants the movements incorporated into his computer models not
only so more realistic animation can be created, but also so that,
for example, a computer program could analyze a patient's gait to
assess the effect a drug was having on someone receiving therapy for
Parkinson's disease.
Other researchers inspired by Laban's work have added his
insights to their computational models of movement. Norman Badler,
an associate dean at the University of Pennsylvania and director of
the university's Center for Human Modeling and Simulation, has been
applying Laban's theories to distinguish between a threatening
gesture and one of surrender, for example. "It's been the goal of my
life to computerize Laban motion analysis," he said. "Laban analysis
is a way of capturing fleeting qualities of movement, rather than
solely their form."
The qualities that Laban described are essential to representing
motion realistically in animation, he said. Neglecting them leads to
animated movements that look flat and robotic.
Alex Vasilescu, a research scientist at the N.Y.U. Media Research
Lab, , is also interested in how small inflections can be
computerized. "I can pick out my dad from far away by how he moves,"
she said. "I think it's going to be possible to teach a computer to
do this, too."
Ms. Vasilescu hopes to identify what she calls a person's "motion
signature," an individual style of movement that is as distinctive
as a fingerprint. In a series of experiments using motion capture,
she videotaped people as they were moving, extracting a mathematical
description of what she calls their general movement style.
Then she predicted how a person with a particular style would
perform a different set of motions - say, climbing stairs. Finally,
she compared the prediction with a motion-capture version of the
person actually ascending or descending a staircase.
So far, she said, the two versions have matched. "I've extracted
a motion signature of how different people move regardless of the
action - for instance, walking or climbing," she said.
Dr. Michael Cohen, a senior researcher at Microsoft
who has worked in computer graphics for 20 years, said that motion
capture would benefit from the new research. "Motion capture is good
at large motions," he said. "But fine subtleties? Certainly not
yet."