Keep Your Face Out of This Computer if Trying to
Hide Your Age
Can estimate ages from 1 year to 93 years with
accuracy about 50% when estimating ages to within 5 years, 80% within 10
years.
In
addition to performing tasks such as security control and
surveillance monitoring, age-estimation software also could be
used for electronic customer relationship management or to
target specific audiences with advertising, said Thomas S.
Huang, the William L. Everitt Distinguished Professor of
Electrical and Computer Engineering at the U. of I.
Photo by L. Brian Stauffer
Oct. 3, 2008 – Trying to hide your age? Better stay
out of the way of this computer software. Like an age-guesser at a
carnival, software being developed at the University of Illinois can
fairly accurately estimate a person’s age. But, unlike age-guessers, who
can view a person’s body, the software works by examining only the
person’s face.
“Age-estimation software is useful in applications
where you don’t need to specifically identify someone, such as a
government employee, but would like to know their age,” said Thomas S.
Huang, the William L. Everitt Distinguished Professor of
Electrical and Computer Engineering at the U. of I.
For example, age-recognition algorithms could stop
underage drinkers from entering bars, prevent minors from purchasing
tobacco products from vending machines, and deny children access to
adult Web sites, said Huang, who leads the Image Formation and
Processing group at the university’s
Beckman Institute.
Estimating someone’s age is not an easy task, even
for a computer. That’s partly because the aging process is determined
not only by a person’s genetic makeup, but by many other factors as
well, including health, location and living conditions.
“Human faces do convey a significant amount of
information, however, and provide important visual cues for estimating
age,” Huang said. “Facial attributes, such as expression, gender and
ethnic origin, play a crucial role in our image analysis.”
Consisting of three modules – face detection,
discriminative manifold learning, and multiple linear regression – the
researchers’ age-estimation software was trained on a database
containing photos of 1,600 faces.
The software can estimate ages from 1 year to 93
years. The software’s accuracy ranges from about 50 percent when
estimating ages to within 5 years, to more than 80 percent when
estimating ages to within 10 years. The accuracy can be improved by
additional training on larger databases of faces, Huang said.
Images of Albert
Einstein's face show him at different ages. This software can
fairly accurately estimate a person's age by examining only the
person's face.
In addition to performing tasks such as security
control and surveillance monitoring, age-estimation software also could
be used for electronic customer relationship management.
For example, a camera snapping photos of customers
could collect demographic data – such as how many adult men and women
buy burgers, or what percentage of teenagers purchase a particular soft
drink.
Or, combined with algorithms that identify a
person’s sex, age-estimation software could help target specific
audiences for specific advertisements. For example, a store display
might advertise a new automobile or boat as a man walks by, or new
clothing or cosmetics as a woman walks by.
“All of this can be done without violating anyone’s
privacy,” Huang said. “Our software does not identify specific
individuals. It just estimates their ages.”
Funding was provided by the National Science
Foundation and the Intelligence Advanced Research Projects Activity. The
researchers published their findings in the two journals IEEE
Transactions on Multimedia and IEEE Transactions on Image Processing in
2008.
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