FACIAL RECOGNITION TECHNOLOGY
By
Joanne vo
HISTORY OF FACIAL RECOGNITION TECHNOLOGY
Among one of the 4 best established biometric techniques that fall under the umbrella of
biometrics, which identify people by measuring some aspect of individual anatomy or
physiology, or some deeply ingrained skill or behavioral characteristic, facial recognition is the
fastest growing biometric technology and will probably be accepted more widely in the future
because it’s simpler for set up and use and also getting less expensive.
As a brief history about this technology, according to the article “Facial-recognition tech has
people pegged” by Emelie Rutherford, facial recognition technology has come to existence over a
decade ago when U.S Defense Department was trying to find a technology that can spot criminals
at border crossing; since then, “university scientist have been working on facial recognition with
the financial support from the U.S Defense Department.” Eventually, companies began
commercializing the technology in the mid of 1990s. This technology made headlines in
February 2001 immediately after it was first used in public at Super Bowl XXXV in Tampa by
the authorities to search for felons and terrorists among the crowd of 100,000 spectators. Soon
after that, the systems are also installed and used in Tampa’s Ybor City, a coastal village, and
some other places such as in the city of Virginia Beach to look for criminal suspects and missing
children…etc
Although this technology is the fastest growing biometric technology today, it is also the most
controversial of all biometrics. While many people support the use of this new technology,
especially after September 11, many others start concerning about the “possibility of identity theft
and privacy infringement” from it’s widespread use. No matter which side we’re on, we should
still learn to know about this technology and how the facial recognition systems work.
HOW FACIAL RECOGNITION SYSTEMS WORK
A facial recognition system consist of cameras that capture images of people who pose or simply
walk by, and a software that matches those pictures. Following are the details of how these
systems work, in general.
a. Basic steps of a facial identification process
Although 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. These basic steps
are:
1) Detection: When the system is attached to a video surveillance system, the recognition
software keeps searching the field of view of a video camera for faces. For each head-like
shape it detects, the system processes it.
2) 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.
3) 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.
4) 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.
5) Matching: The newly acquired facial data is compared to the stored data and (ideally)
linked to at least one stored facial representation.
b. What facial data the system takes?
Assuming that the system has detected a head and has done with the alignment and normalization
processes, what facial data does it take into consideration before it translates that data into a
unique code? Different systems may analyze a face that they have captured differently. Let’s
look at Visonics’s way because it’s one of the leading companies specialized in developing facial
recognition systems. Visionics’ facial recognition system, FaceIt, measures a face according to
its peaks and valleys, which are called nodal points. The tip of the nose, the depth of the eye
sockets, distance between eyes, width of nose, cheekbones, jaw line, and chin are some examples
of nodal points, and “there are about 80 nodal points on a human face”. The software
concentrates on the inner region of the face called “golden triangle”, which runs from temple to
temple and just over the lip; this is the most stable area because even if you grow beard, put on
classes, put on weight or age, that region tends not to be affected. FaceIt only needs from 14 to 22
nodal points to complete a recognition process, according to Kevin Bonsor’s article “How Facial
Recognition Systems work.” This software takes the measurements and creates a numerical code
called a faceprint, which is made up of a string of numbers and it represents a face (as step #4
above).
c. How is the matching process done?
The faceprints stored in the database represents the people (or criminal) we’re looking for and
will be compared against the ones of the people passing in front of the cameras to find a match.
“The FaceIt 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 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.
I.
RELIABILITY OF FACIAL RECOGNITION SYSTEMS AND THEIR LIMITATIONS
Facial recognition software is proven not yet as accurate as the other types of biometrics such as
fingerprints or iris scanning. Although the marketing people of those companies selling facial
recognition systems claim that their systems can recognize a person even if he/she tries to
disguise himself / herself, the real study showed that “a disguise or even a minor change in
appearance, like wearing sunglasses or wearing or growing a mustache can often fool the system.
Even an unusual facial expression can confuse the software.” Lighting and the angle at which
the photos are taken are some other factors that can affect the image quality and system efficacy.
Furthermore, according to one National Institute of Justice Standards and Technology study, the
success rate of a facial identifier that can match a face of a person captured by the camera with
the same person’s photograph taken 18 months prior is only about 57%.
In March 2002 after September 11 terrorist attack, when airports considered putting in use the
facial recognition software, they performed a test on the system. In this test, fifteen airport
employees tried to get through the security checkpoint. The security checkers had a database of
250 faceprints, including those of the 15 testers. Over a four-week period, the testers made 958
attempts to pass through the checkpoint; the face recognition system stopped them 455 times, for
a success rate of only 47 percent. On top of that, there were 1,081 false alarms triggered by
ordinary passengers and other airport employees passing through the scanners. That worked out
to two or three false alarms per hour. This was the main reason why most of the airports haven’t
put in use this software. According to Richard Smith, former head of the Privacy Foundation at
Denver University and now a privacy and Internet security consultant in Brookline,
Massachusetts, if an airport uses facial recognition software, it would require “special walkways
where lighting is tightly controlled and passengers pass single file; passengers would have to be
instructed to remove hats and glasses and look straight ahead at a head-height camera.”
In short, since the facial recognition technology is still very new, the facial recognition systems
available nowadays are still not very reliable. Companies need to improve their products before
these systems can be used more widely.
USES OF FACIAL RECOGNITION SYTEMS
Law enforcement and security agencies have been the primary users of facial recognition
software for several years by now. For example, the cities of Tampa and Virginia Beach have
started using it in outdoor cameras since last year to spot missing children and lawbreakers. This
software also has been used in most of major casinos across the country.
In addition to law enforcement and security surveillance, in the recent years, facial recognition
software also has several other uses including the uses in elections to eliminate voter fraud; the
technology was used in our country’s 2000 presidential election and is expected to be used in
local elections. The facial identification technology can also be used in ATM transactions for
identity verification so that there is no need for a picture ID, bankcard …etc.
Before September 11, since the technology is still new with many weaknesses and together with
privacy issues, the public viewed it with much more skepticism than it does today. In the wake of
the September 2001 terrorist attacks on the U.S., privacy advocates, citizen groups, political
leaders, and the manufacturers of the technology itself are debating whether these technologies
should be more widely used, and if so, how they should be regulated to protect the privacy of the
public. Some airports are considering installing face recognition cameras as a security measure.
However, T.F. Green International Airport in Providence, Rhode Island, one of the first airports
to consider it, decided in January 2002 that they would not install it after all, citing the possibility
of false matches and other technological shortcomings of facial recognition systems.
As the technology getting more matured, facial recognition will have many uses in the near future
since its software is “often compatible with the computers and cameras already in use by airports,
banks, and other corporations, and the technology is also getting less expensive;” it is becoming
more and more attractive to private institutions as a way of preventing fraud.
PRIVACY ISSUES
As the facial recognition systems become widespread, a lot of people start concerning about the
privacy risks associated with its use. People don’t like the feeling of being watched every time
they step outside their homes. Innocent people are afraid of the possibilities that their faces get
scanned and stored somewhere in the database that can be used later for identity theft or racial
profiling practices or accidentally identifying innocent people as criminals. As of today, there is
not yet any law passed out to require the law enforcement agencies using the facial recognition
systems to discard all the information on seemingly innocent faces in the crowd. To minimize
privacy concerns involved with using the facial recognition technology so that the public can feel
more comfortable with this new technology, in my opinion, the federal government needs to step
in and regulates its uses.
CONCLUTION
As the fastest growing biometric technology today, facial recognition will have many uses in the
near future. While facial recognition can be used to protect your privacy, it can as easily be used
to invade your privacy by taking your picture when you’re entirely unaware of the camera.
Consequently, the government needs to pass some laws to protect innocent people. Also, in order
for the technology to be more reliable and for the public to feel comfortable in accepting the
technology, the companies inventing and selling the facial recognition systems must improve
their products to increase the accuracy of the systems.
References:
“Facial-recognition tech has people pegged”, by Emelie Rutherford July 17, 2001
“Facial recognition Systems: Are privacy rights of citizens being eroded wholesale” by Angela Jarvis
“How facial Recognition Systems Work” by Kevin Bonsor
“Face the Facts: Facial recognition technology’s troubled past -- and troubling future” by David Kopel
and Michael Krause