Featured Research

from universities, journals, and other organizations

Facial recognition technology aimed at spotting terrorists

Date:
September 16, 2010
Source:
University of Texas at Dallas
Summary:
Rapid improvements in facial-recognition software mean airport security workers might one day know with near certainty whether they're looking at a stressed-out tourist or staring a terrorist in the eye. Researchers are evaluating how well these rapidly evolving recognition programs work. The researchers are comparing the rates of success for the software to the rates for non-technological, but presumably "expert" human evaluation.

“The government is interested in spotting people who might pose a danger,” Dr. Alice O’Toole said. “But they also don’t want to have too many false alarms and detain people who are not real risks.”
Credit: Image courtesy of University of Texas at Dallas

Rapid improvements in facial-recognition software mean airport security workers might one day know with near certainty whether they're looking at a stressed-out tourist or staring a terrorist in the eye.

Related Articles


A research team led by Dr. Alice O'Toole, a professor in The University of Texas at Dallas' School of Behavioral and Brain Sciences, is evaluating how well these rapidly evolving recognition programs work. The researchers are comparing the rates of success for the software to the rates for non-technological, but presumably "expert" human evaluation.

"The government is interested in spotting people who might pose a danger," O'Toole said. "But they also don't want to have too many false alarms and detain people who are not real risks."

The studies in the Face Perception and Research Laboratories are funded by the U.S. Department of Defense. The agency is seeking the most accurate and cost-effective way to recognize individuals who might pose a security risk to the nation.

Algorithms -- formulae that allow computers to "recognize" faces -- vary greatly among the various software developers, and most have not faced real-world challenges. So O'Toole and her team are carefully examining where the algorithms succeed and where they come up short. They're using point-by-point comparisons to examine similarities in millions of faces captured within a database, and then comparing results to algorithm determinations.

In the studies, humans and algorithms decided whether pairs of face images, taken under different illumination conditions, were pictures of the same person or different people.

The UT Dallas researchers have worked with algorithms that match up still photos and are now moving into comparisons involving more challenging images, such as faces caught on video or photographs taken under poor lighting conditions.

"Many of the images that security people have to work with are not high-quality," O'Toole said. "They may be taken off closed-circuit television or other low-resolution equipment."

The study is likely to continue through several more phases, as more and better software programs are presented for review. So far, the results of man vs. machine have been a bit surprising, O'Toole said.

"In fact, the very best algorithms performed better than humans at identifying faces," she said. "Because most security applications rely primarily on human comparisons up until now, the results are encouraging about the prospect of using face recognition software in important environments."

The real success comes when the software is combined with human evaluation techniques, O'Toole said. By using the software to spot potential high-risk individuals and then combining the software with the judgment of a person, nearly 100 percent of matching faces were identified, O'Toole said.

The researchers also are interested in the role race plays in humans' ability to spot similar facial features. O'Toole said many studies indicate individuals almost always recognize similarities among members of their own race with more accuracy. But there is little research evaluating how technological tools differ in recognizing faces of varying races.

In a paper to be published soon in ACM Transactions on Applied Perception, O'Toole reports that the "other race effect" occurs for algorithms tested in a recent international competition for state-of-the-art face recognition algorithms. The study involved a Western algorithm made by fusing eight algorithms from Western countries and an East Asian algorithm made by fusing five algorithms from East Asian countries. At the low false-accept rates required for most security applications, the Western algorithm recognized Caucasian faces more accurately than East Asian faces, and the East Asian algorithm recognized East Asian faces more accurately than Caucasian faces.

Next, using a test that spanned all false-alarm rates, O'Toole's team compared the algorithms with humans of Caucasian and East Asian descent matching face identity in an identical stimulus set. In this case, both algorithms performed better on the Caucasian faces, the "majority" race in the database. The Caucasian face advantage was far larger for the Western algorithm than for the East Asian algorithm.

Humans showed the standard other-race effect for these faces, but showed more stable performance than the algorithms over changes in the race of the test faces. These findings indicate that state-of-the-art face-recognition algorithms, like humans, struggle with "other-race face" recognition, O'Toole said.

The companies that develop the most reliable facial recognition software are likely to reap big profits down the line. Although governments may be their most obvious clients, there is also a great deal of interest from other major industries.

"Casinos have been some of the first users of face recognition software," O'Toole said. "They obviously want to be able to spot people who are counting cards and trying to cheat the casino."

O'Toole collaborated on the research with Dr. P. Jonathon Phillips of the National Institute of Standards and Technology, Dr. Fang Jiang of the University of Washington, and Dr. Abhijit Narvekar of Alcon Labs.


Story Source:

The above story is based on materials provided by University of Texas at Dallas. Note: Materials may be edited for content and length.


Cite This Page:

University of Texas at Dallas. "Facial recognition technology aimed at spotting terrorists." ScienceDaily. ScienceDaily, 16 September 2010. <www.sciencedaily.com/releases/2010/09/100915140340.htm>.
University of Texas at Dallas. (2010, September 16). Facial recognition technology aimed at spotting terrorists. ScienceDaily. Retrieved October 30, 2014 from www.sciencedaily.com/releases/2010/09/100915140340.htm
University of Texas at Dallas. "Facial recognition technology aimed at spotting terrorists." ScienceDaily. www.sciencedaily.com/releases/2010/09/100915140340.htm (accessed October 30, 2014).

Share This



More Computers & Math News

Thursday, October 30, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Mind-Controlled Prosthetic Arm Restores Amputee Dexterity

Mind-Controlled Prosthetic Arm Restores Amputee Dexterity

Reuters - Innovations Video Online (Oct. 29, 2014) A Swedish amputee who became the first person to ever receive a brain controlled prosthetic arm is able to manipulate and handle delicate objects with an unprecedented level of dexterity. The device is connected directly to his bone, nerves and muscles, giving him the ability to control it with his thoughts. Matthew Stock reports. Video provided by Reuters
Powered by NewsLook.com
Robots Get Funky on the Dance Floor

Robots Get Funky on the Dance Floor

AP (Oct. 29, 2014) Dancing, spinning and fighting robots are showing off their agility at "Robocomp" in Krakow. (Oct. 29) Video provided by AP
Powered by NewsLook.com
IBM Taps Into Twitter's Data With New Partnership

IBM Taps Into Twitter's Data With New Partnership

Newsy (Oct. 29, 2014) The new partnership will allow IBM to access Twitter’s data and analytics to help IBM clients better understand their consumers. Video provided by Newsy
Powered by NewsLook.com
Google To Use Nanoparticles, Wearables To Detect Disease

Google To Use Nanoparticles, Wearables To Detect Disease

Newsy (Oct. 29, 2014) Google X wants to improve modern medicine with nanoparticles and a wearable device. It's all an attempt to tackle disease detection and prevention. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:

Strange & Offbeat Stories


Space & Time

Matter & Energy

Computers & Math

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins