For Immediate Release
Researchers at the Georgia Institute of Technology and elsewhere are
developing technologies to recognize a person's walk, or gait. Results
indicate these new identification methods hold promise as tools in the
war on terrorism and in medical diagnosis.
Gait recognition technology is a biometric method -- that is, a unique biological or behavioral identification characteristic, such as a fingerprint or a face. Though still in its infancy, the technology is growing in significance because of federal studies, such as the Georgia Tech projects.
At Georgia Tech, one study is addressing issues of gait recognition by
computer vision, and the other is exploring a novel approach -- gait recognition
with a radar system similar to those used by police officers to catch
The ultimate goal is to detect, classify and identify humans at distances up to 500 feet away under day or night, all-weather conditions. Such capabilities will enhance the protection of U.S. forces and facilities from terrorist attacks.
"We need technology to find the bad guys at a distance," said
Jon Geisheimer, a research engineer at the Georgia
Tech Research Institute (GTRI).
Because gait recognition technology is so new, researchers are assessing
the uniqueness of gait and methods by which it can be evaluated.
"We know that we can get some information on gait, but that it is
much less diagnostic than faces," says Aaron Bobick, an associate
professor of computing and co-director of the computer vision project
at Georgia Tech. "Currently, we can't recognize one in 100,000 people.
At the moment, gait recognition is not capable of that, but it's getting
better so it can act as a filter."
In its early development, gait recognition technology likely will serve
as a screening tool in conjunction with other biometric methods.
With two years of experiments and analysis almost complete, researchers
on both Georgia Tech projects are hopeful for continued funding to conduct
further studies. They must address numerous technical issues and it will
be at least five years before the technologies are commercialized, researchers
In the project using radar for gait recognition, results from experiments,
data analysis and algorithm design are promising, says Geisheimer, who
works under the direction of GTRI principal research scientist Gene Greneker,
and collaborates with GTRI research engineer Bill Marshall and Georgia
State University Professor of Biomechanics Ben Johnson.
Gait recognition by radar focuses on the gait cycle formed by the movements
of a person's various body parts move over time.
"The magic goal we're shooting for is accuracy in the high 90 percent
range," Geisheimer says. "We're not there yet, but our initial
results are encouraging and promising."
Researchers correctly identified 80 to 95 percent of individual subjects,
with variances in that range among the three experiment days.
The next step is to build a more powerful radar system and test it in
the lab and then the field. In experiments last year, subjects started
walking 50 feet away from the radar and then walked within 15 feet of
it. But researchers are now building a radar system that can detect people
from 500 or more feet.
In the study of gait recognition by computer vision, researchers distinguish
their approach from others with a technique called an activity-specific
static biometric. A static property -- for example, a person's leg length
-- is not a property of motion itself. It can be measured from a single
"The advantage of measuring a static property is that it is amenable
to being done from multiple viewpoints," Bobick says. "
Static measurements are view invariant, and that is a tremendous advantage
because you can't control where someone goes."
Researchers are also developing statistical analysis tools for using
a small, easily gathered database to predict how well a particular biometric,
including gait recognition, will work on a larger population.
These techniques will also help researchers determine what gait recognition
properties to measure based on how well the technology can measure them.
"You can work on your ability to improve measurements," Bobick
says. "But if you're not measuring something that is diagnostic,
there is no amount of technology that will solve that problem with the
Still in its infancy, computer vision-based gait recognition technology
holds promise, particularly for verification or screening, if it is used
in conjunction with other biometric technologies and information, Bobick
Meanwhile, researchers are applying the findings from studies funded
by the federal Defense Advanced Research Projects Agency to ongoing research
in understanding human movement through video. Associate Professor Irfan
Essa envisions applications in medical diagnosis.
"Gait analysis has been important in the health field for a long
time," Essa says. "Basic changes in someone's walking pattern
can be an early indicator of the onset of Parkinson's disease, multiple
sclerosis and normal pressure hydrocephalus (NPH)."
Farther in the future are applications in diagnosing depression and lie detection.
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WRITER: Jane Sanders