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6726 
 

Facing a challenge

07/28/08 
By Drew Robb,

The federal government has been researching facial recognition technologies
since the 1960s and, although it has significantly improved over the
decades, it is still far from meeting operational needs. 
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"Facial recognition is the weakest of the biometric modalities," said
Matthew Malanowski, an intelligence specialist at the Army Intelligence
Center at Fort Huachuca, Ariz. "People have to be full frontal into the
camera, and you can't do anything covert." 
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Facial recognition is one of the three methods, along with fingerprint and
iris recognition, used by the Defense Department's Biometrics Automated
Toolset. BAT, which resides on 75 networked servers, is used by 1,500
clients in Iraq and at the National Ground Intelligence Center and other
commands worldwide. To improve BAT's accuracy, the Army in April issued a
request for information (GCN.com, Quickfind 1159) to assess the state of the
technology in being able to recognize people under less than ideal
conditions. Those conditions include when the face is turned, under poor
lighting or the when the face is partially obscured by a branch. 
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"What we are looking for is software that can manipulate a two-dimensional
capture and make it three dimensional," said Malanowski. That way, other
images of a person can be compared with the 3-D image, no matter what angle
the person is facing, according to the RFI. 
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"Depending on the resolution of the input facial images and the amount of
manual intervention during the modeling process, the results can be highly
accurate," said Demetri Terzopoulos, Chancellor's Professor of Computer
Science at UCLA's Computer Science Department. 
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In the RFI, the Army was looking for a 95 percent identification rate with
no more than a 1 percent false acceptance rate. The RFI also called for a
module that would identify facial profiles with a 90 percent identification
rate and no more than 10 percent of false positives. 
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The Army evaluated responses from five vendors and found them lacking. 
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"The entire purpose of the RFI was to determine whether the capability
exists now," said Malanowski. "We determined it does not; that technology
needs to be developed." 
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So, the Army plans to release a request for proposals to create the software
needed to move closer to what is needed. 
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In the meantime, other agencies are also trying to develop better
face-recognition software. The interagency Technical Support Working Group
has spent more than $40 million on such research over the past decade. The
National Institute of Standards and Technology has conducted a series of
Face Recognition Vendor Tests (GCN.com, Quickfind 1160). 
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To the test 
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>From 2004 to 2006, the FBI and other agency groups sponsored the Face
Recognition Grand Challenge, in which researchers and developers were given
a set of increasingly difficult set of problems to solve, using a data set
of 50,000 images. This year the group is hosting the Multibiometric Grand
Challenge, which combines face recognition with iris recognition. 
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"Progress has been made in increasing the degree of modeling automation and
the imaging technology has improved, increasing the resolution, which yields
more accurate facial geometry and texture," Terzopoulos said. 
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Since last summer, Portugal has been using the eBox RAPID system at its
airports in Lisbon and Faro. In less than 20 seconds it verifies individuals
match the data in the electronic passport and opens a gate to let them
through. This is fairly simple in cases where there is a one-on-one match
between one person and one passport. However, the chance of error increases
logarithmically with the number of identities in a database. So, when
dealing with something the size of the terrorist watch list - nearly 1
million identities - the automatic recognition systems need to be near
perfect. 
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"You have people who are going through security at an airport, you should be
able to match them with a watch list," said Malanowski. "Ideally that would
be great, but we don't have that capability yet." 


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