A newly-emerging trend in facial recognition software uses a 3D model, which
claims to provide more accuracy. Capturing a real-time 3D image of a person's
facial surface, 3D facial recognition uses distinctive features of the face --
where rigid tissue and bone is most apparent, such as the curves of the eye
socket, nose and chin -- to identify the subject. These areas are all unique
and don't change over time.
Using depth and an axis of measurement that is not affected by lighting, 3D
facial recognition can even be used in darkness and has the ability to
recognize a subject at different view angles with the potential to recognize up
to 90 degrees (a face in profile).
Using the 3D software, the system goes through a series of steps to verify
the identity of an individual.
Detection
Acquiring an image can be accomplished by digitally scanning an existing
photograph (2D) or by using a video image to acquire a live picture of a
subject (3D).
Alignment
Once it detects a face, the system determines the head's position, size and
pose. As stated earlier, the subject has the potential to be recognized up to
90 degrees, while with 2D, the head must be turned at least 35 degrees toward
the camera.
Measurement
The system then measures the curves of the face on a sub-millimeter (or
microwave) scale and creates a template.
Representation
The system translates the template into a unique code. This coding gives
each template a set of numbers to represent the features on a subject's face.
Matching
If the image is 3D and the database contains 3D images, then matching will
take place without any changes being made to the image. However, there is a
challenge currently facing databases that are still in 2D images. 3D provides a
live, moving variable subject being compared to a flat, stable image. New
technology is addressing this challenge. When a 3D image is taken, different
points (usually three) are identified. For example, the outside of the eye, the
inside of the eye and the tip of the nose will be pulled out and measured. Once
those measurements are in place, an algorithm (a step-by-step procedure)
will be applied to the image to convert it to a 2D image. After conversion, the
software will then compare the image with the 2D images in the database to find
a potential match.
Verification or Identification
In verification, an image is matched to only one image in the database
(1:1). For example, an image taken of a subject may be matched to an image in
the Department of Motor Vehicles database to verify the subject is who he says
he is. If identification is the goal, then the image is compared to all images
in the database resulting in a score for each potential match (1:N). In this
instance, you may take an image and compare it to a database of mug shots to
identify who the subject is.
Facial Recognition
Systems Uses
In the past, the primary users of facial recognition software have been law
enforcement agencies, who used the system to capture random faces in crowds.
Some government agencies have also been using the systems for security and to
eliminate voter fraud. The U.S. government has recently begun a program called US-VISIT
(United States Visitor and Immigrant Status Indicator Technology), aimed at
foreign travelers gaining entry to the United States. When a foreign traveler
receives his visa, he will submit fingerprints and have his photograph taken.
The fingerprints and photograph are checked against a database of known
criminals and suspected terrorists. When the traveler arrives in the United
States at the port of entry, those same fingerprints and photographs will be
used to verify that the person who received the visa is the same person
attempting to gain entry.
However, there are now many more situations where the software is becoming
popular. As the systems become less expensive, making their use more
widespread. They are now compatible with cameras and computers that are already
in use by banks and airports. The TSA is currently working on and testing out
its Registered Traveler program. The program will provide speedy security
screening for passengers who volunteer information and complete a security
threat assessment. At the airport there will be specific lines for the
Registered Traveler to go through that will move more quickly, verifying the
traveler by their facial features.
Other potential applications include ATM and check-cashing security. The
software is able to quickly verify a customer's face. After a customer
consents, the ATM or check-cashing kiosk captures a digital image of him. The
FaceIt software then generates a faceprint of the photograph to protect
customers against identity theft and fraudulent transactions. By using the
facial recognition software, there's no need for a picture ID, bankcard or
personal identification number (PIN) to verify a customer's identity. This way
businesses can prevent fraud from occurring.
While all the examples above work with the permission of the individual, not
all systems are used with your knowledge. In the first section we mentioned
that systems were used during the Super Bowl by the Tampa Police, and in Ybor
City. These systems were taking pictures of all visitors without their knowledge
or their permission. Opponents of the systems note that while they do provide
security in some instances, it is not enough to override a sense of liberty and
freedom. Many feel that privacy infringement is too great with the use of these
systems, but their concerns don't end there. They also point out the risk
involved with identity theft. Even facial recognition corporations admit that
the more use the technology gets, the higher the likelihood of identity theft
or fraud.
As with many developing technologies, the incredible potential of facial
recognition comes with some drawbacks, but manufacturers are striving to
enhance the usability and accuracy of the systems.
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