How Facial Recognition Systems
Work by Kevin
Bonsor
A ticket to Super Bowl XXXV in Tampa Bay, Florida,
didn't just get you a seat at the biggest professional
football game of the year. Those who attended the January 2000
event were also part of the largest police lineup ever
conducted, although they may not have been aware of it at the
time. The Tampa
Police Department was testing out a new technology, called
FaceIt,
that allows snapshots of faces from the crowd to be compared
to a database of criminal mugshots.
Photo courtesy Visionics Facial recognition software can be used to
find criminals in a crowd, turning a mass of people into
a big
lineup.
The $30,000 system was loaned to the Tampa Police
Department for one year. So far, no arrests have been made
using the technology. However, the 36 cameras positioned in
different areas of downtown Tampa have allowed police to keep
a more watchful eye on general activities. This increased
surveillance of city residents and tourists has riled privacy
rights groups.
People have an amazing ability to recognize and remember
thousands of faces. In this edition of HowStuffWorks,
you'll learn how computers are turning your face into computer
code so it can be compared to thousands, if not millions, of
other faces. We'll also look at how facial recognition
software is being used in elections, criminal
investigations and to secure your personal computer.
The Face Your face is an important part of
who you are and how people identify you. Imagine how hard it
would be to recognize an individual if all faces looked the
same. Except in the case of identical twins, the face is
arguably a person's most unique physical characteristic. While
humans have had the innate ability to recognize and
distinguish different faces for millions of years, computers
are just now catching up.
Visionics, a company based in New Jersey, is one of
many developers of facial recognition technology. The twist to
its particular software, FaceIt, is that it can pick
someone's face out of a crowd, extract that face from the rest
of the scene and compare it to a database full of stored
images. In order for this software to work, it has to know
what a basic face looks like. Facial recognition software is
based on the ability to first recognize faces, which is a
technological feat in itself, and then measure the various
features of each face.
Photo courtesy Visionics Facial recognition software is designed to
pinpoint a face and measure its
features.
If you look in the mirror, you can see that your face has
certain distinguishable landmarks. These are the peaks and
valleys that make up the different facial features. Visionics
defines these landmarks as nodal points. There are
about 80 nodal points on a human face. Here are a few of the
nodal points that are measured by the software:
Distance between eyes
Width of nose
Depth of eye sockets
Cheekbones
Jaw line
Chin
These nodal points are measured to create a numerical code,
a string of numbers, that represents the face in a database.
This code is called a faceprint. Only 14 to 22 nodal
points are needed for the FaceIt software to complete the
recognition process. In the next section, we'll look at how
the system goes about detecting, capturing and storing faces.
The Software Facial recognition software
falls into a larger group of technologies known as
biometrics. Biometrics uses biological information to
verify identity. The basic idea behind biometrics is that our
bodies contain unique properties that can be used to
distinguish us from others. Besides facial recognition,
biometric authentication methods also include:
Fingerprint scan
Retina scan
Voice identification
Facial recognition methods may vary, but they generally
involve a series of steps that serve to capture, analyze and
compare your face to a database of stored images. Here is the
basic process that is used by the FaceIt system to capture and
compare images:
To identify someone, facial
recognition software compares newly captured images to
databases of stored images.
Detection - When the system is attached to a
video surveillance system, the recognition software searches
the field of view of a video
camera for faces. If there is a face in the view, it is
detected within a fraction of a second. A multi-scale
algorithm is used to search for faces in low resolution.
(An algorithm is a program that provides a set of
instructions to accomplish a specific task). The system
switches to a high-resolution search only after a head-like
shape is detected.
Alignment - Once a face is detected, the system
determines the head's position, size and pose. A face needs
to be turned at least 35 degrees toward the camera
for the system to register it.
Normalization -The image of the head is scaled
and rotated so that it can be registered and mapped into an
appropriate size and pose. Normalization is performed
regardless of the head's location and distance from the
camera. Light does
not impact the normalization process.
Representation - The system translates the facial
data into a unique code. This coding process allows for
easier comparison of the newly acquired facial data to
stored facial data.
Matching - The newly acquired facial data is
compared to the stored data and (ideally) linked to at least
one stored facial representation.
The heart of the FaceIt facial recognition system is the
Local Feature Analysis (LFA) algorithm. This is the
mathematical technique the system uses to encode faces. The
system maps the face and creates a faceprint, a unique
numerical code for that face. Once the system has stored a
faceprint, it can compare it to the thousands or millions of
faceprints stored in a database. Each faceprint is stored as
an 84-byte file.
Photo courtesy Visionics Using facial recognition software, police can
zoom in with cameras and take a snapshot of a
face.
The system can match multiple faceprints at a rate of 60
million per minute from memory or 15 million per minute from
hard
disk. As comparisons are made, the system assigns a value
to the comparison using a scale of one to 10. If a score is
above a predetermined threshold, a match is declared.
The operator then views the two photos that have been declared
a match to be certain that the computer is accurate.
Facial recognition, like other forms of biometrics, is
considered a technology that will have many uses in the near
future. In the next section, we will look how it is being used
right now.
Gotcha! The primary users of facial
recognition software like FaceIt have been law enforcement
agencies, which use the system to capture random faces in
crowds. These faces are compared to a database of criminal mug
shots. In addition to law enforcement and security
surveillance, facial recognition software has several other
uses, including:
Eliminating voter fraud
Check-cashing identity verification
Computer security
One of the most innovative uses of facial recognition is
being employed by the Mexican government, which is using the
technology to weed out duplicate voter registrations. To sway
an election, people will register several times under
different names so they can vote more than once. Conventional
methods have not been very successful at catching these
people.
Using the facial recognition technology, officials can
search through facial images in the voter database for
duplicates at the time of registration. New images are
compared to the records already on file to catch those who
attempt to register under aliases. The technology was used in
the country's 2000 presidential election and is expected to be
used in local elections soon.
Potential applications even include ATM and check-cashing
security. The software is able to quickly verify a customer's
face. After the user consents, the ATM or check-cashing kiosk
captures a digital
photo of the customer. The FaceIt software then generates
a faceprint of the photograph to protect customers against
identity theft and fraudulent transactions. By using facial
recognition software, there's no need for a picture ID, bank
card or personal identification number (PIN) to verify a
customer's identity.
Photo courtesy Visionics Many people who don't use banks use check
cashing machines. Facial recognition could eliminate
possible criminal
activity.
This biometric technology could also be used to secure your
computer
files. By mounting a Webcam to
your computer and installing the facial recognition software,
your face can become the password you use to get into your
computer. IBM
has incorporated the technology into a screensaver
for its A,T and X series Thinkpad laptops.
Photo courtesy Visionics Facial recognition software can be used to
lock your
computer.
While facial recognition can be used to protect your
private information, it can just as easily be used to invade
your privacy by taking you picture when you are entirely
unaware of the camera. As with many developing technologies,
the incredible potential of facial recognition comes with
drawbacks.
For more information on facial recognition technology and
related topics, see the links on the next page.
