Posts Tagged ‘facial recognition’

By Kayla Matthews

Facial recognition is set to have a significant impact on our society as a whole.

While many consumers are familiar with the concept because of the many smartphone apps that let them add various filters, graphics and effects to their pictures, the technology behind facial recognition isn’t limited to playful, mainstream applications.

Law enforcement is using next-gen software to identify and catch some of their most wanted criminals. But government officials in China are taking the technology even further by installing a nationwide system of facial recognition infrastructure—and it’s already generating plenty of controversy on account of its massive scale.

The Usefulness of Facial Recognition

Many applications of facial recognition are legitimate. China and many other countries use basic systems to monitor ATMs and restrict public access to government-run or other sensitive facilities. Some restaurants are even using the technology to provide food recommendations based on the perceived age and gender of the user.

Facial recognition is also useful in security. At least one prominent tourist attraction is using the technology to thwart would-be thieves. Similar systems have been installed at the doors of a women’s dormitory at Beijing Normal University to prevent unauthorized entry.

While it’s impossible to say how much crime the new system prevents, other female dorms are already considering the hardware for their own use. Applications like this have a definite benefit to the entire nation.

Chinese officials are already praising facial recognition as the key to the 21st-century smart city. They’ve recently pioneered a Social Credit System that aims to give every single citizen a rating. Meant to assist in determining an individual’s trustworthiness or financial status, the success of their program has been spurred on by current facial recognition software and hardware.

Officials aim to enroll every Chinese citizen into a nationwide database by 2020, and they’re already well on their way to doing so.

The Controversial Side

Advanced technology such as this rarely exists without controversy. Pedestrians in southern China recently expressed outrage when their information was broadcast publicly. While supporters of facial recognition systems will insist that law-abiding citizens aren’t at risk of this kind of public exposure, hackers could, in theory, take control of these systems and use them for their own nefarious purposes.

With some 600 million closed-circuit television (CCTV) systems already in place throughout the nation, the odds of a serious break-in or cyber attack are astronomical.

There have already been countless reports of Chinese hackers gaining unauthorized access to consumer webcams across the country, and some experts believe the same technology could be used to hack the nation’s CCTV network. Given the sheer amount of systems and the potential for massive disruptions to public infrastructure, it seems like it’s only a matter of time.

There’s also the issue of global privacy. Although China has always been very security-conscious, their massive surveillance system is already raising questions of morality, civil liberty and confidentiality. If the government begins targeting peaceful demonstrators who are attending lawful protests, for instance, there could be some serious repercussions.

A Full-Scale Model for the Modern Smart City

In 2015, the Chinese Ministry of Public Security announced their intentions for an “omnipresent, completely connected, always on and fully controllable” network of facial recognition systems and CCTV hardware.

While this will certainly benefit the Chinese population in many ways, including greater security throughout the country, it will undoubtedly rub some people the wrong way.

In either case, other government entities will be watching this closely and learning from their mistakes.

by Angela Nelson

You’ve probably heard about face blindness, an incurable neurological disorder that impairs someone’s ability to recognize faces — even those of family or friends. It affects about 2.5 percent of the world’s population, or 1 in every 50 people.

At the other end of the spectrum are “super recognizers.” These gifted individuals can remember people they’ve met or seen only briefly, as well as people they haven’t seen in decades whose appearance may have changed. Though researchers don’t yet know how many of us have these superior facial recognition skills, early estimates indicate that, like facial blindness, 1 in 50 people have the skill, according to a recent study published in the journal Frontiers in Psychology.

Researchers at Bournemouth University in the U.K. studied 254 British young adults and investigated how the super recognizers among them processed faces. According to an article written by one of the study authors, Sarah Bate, Ph.D., in The Conversation:

It has long been known that the optimal way to process faces involves the use of a “configural” or “holistic” processing strategy. This involves seeing faces as a whole, taking account of all of the facial features and the spacing between them. Interestingly, all of the super recognizer participants displayed heightened configural processing on at least one task. We also monitored their eye movements as they looked at faces. While control participants mostly looked at the eyes, super recognizers spent more time looking at the nose. It is possible that this more central viewing position promotes the optimal configural processing strategy.

Being a super recognizer has nothing to do with your intellect or your ability to excel at visual or memory tasks, according to Bate. However, it may have something to do with your genes, as increasing evidence shows the ability is hereditary. Face blindness has been known to run in families, too.

How can you test for this?

Bate writes that some tests show participants a photo of a celebrity taken a long time before they became famous. But that test is flawed, because you never know when you’re going to get a celebrity superfan in the mix. “A more reliable option is to assess performance on computerized tests that require participants to memorize faces and to later recall them. The number of correct responses can then be compared to the average score achieved by people with typical face recognition skills,” Bate says.

During the tests, researchers found some participants were “extremely good at deciding whether pairs of simultaneously presented faces were of the same person or two different people.” One superhero-like skill that hasn’t yet been tested is the ability to scan large crowds for individual faces.

Some police forces are already screening candidates for superior facial recognition skills. These super spotters could scan CCTV or security camera footage for a missing person, victim or suspect. Or they could examine passports at airports or border crossings. As Bate points out, there may not be enough of these people to go around for all the potential uses, but an “elite team” could be formed and deployed as needed.

by Jamie K. White

Can your pet fish recognize your face? A new study says, Yes, it probably can.

Researchers studying archerfish found the fish can tell a familiar human face from dozens of new faces with surprising accuracy.

This is a big, big deal. It’s the first time fish have demonstrated this ability.

Think about it: All faces have two eyes sitting above a nose and a mouth. And for us to be able to tell them apart, we need to be able to pick up the subtle differences in features.

We’re good at this because we are smart, i.e. we have large and complex brains. Other primates can do this too. Some birds as well.

But a fish? A fish has a tiny brain. And it would have no reason in its evolution to learn how to recognize humans.

So this study, published Tuesday in the journal “Scientific Reports,” throws on its head all our conventional thinking. It was done by scientists at University of Oxford in the U.K. and the University of Queensland in Australia.

And, for us, it raises many, many questions:

Does this mean my pet goldfish knows me? Do fish recognize each other? CAN DORY REALLY FIND NEMO?

To find out more, we talked to Dr. Cait Newport, a research fellow in Oxford University’s zoology department and co-author of the study.

What were the scientists trying to figure out?

The scientists wanted to know how well animals with simple brains do with facial recognition. A fish was a good choice. Their brains lack the section that we use for facial recognition. That made them perfect as subjects for an experiment to see if simple brains can perform complex tasks.

What’s an archerfish?

It’s a species of tropical fish. They spit jets of water from their mouth to knock down insects from branches. They’re the sharpshooters of the animal kingdom.

Why did scientists use archerfish?

Archerfish can indicate a choice clearly (the spitting) whereas other fish cannot. “There is no ambiguity in where they are shooting,” Newport said.

How did the experiment work?

Scientists presented the fish with two images of human faces and trained them to choose one by spitting their jets at that picture.

Wait, hold up. How do you ‘train’ an archerfish?

The old, time-tested way. Bribe them. When they spit at the image the scientists wanted them to spit at, they were rewarded with a pellet of food, Newport said.

How long did that take?

In some cases, only a few days. In others, up to two weeks. “Something like 60 to 90 trials,” Newport said.

How many people did it take?

A total of four (really smart) people: Newport and her co-authors Guy Wallis, Yarema Reshitnyk and Ulrike E Siebeck.

What did they do?

They presented the fish with the picture of the face they wanted the fish to learn and a bunch of new faces. Up to 44 new ones. The fish were able to pick the familiar face correctly 81% of the time.

Impressive. And then?

The researchers decided to make things a little harder. They took the pictures and made them black and white and evened out the head shapes. You’d think that would throw the fish for a loop. But no, they were able to pick the familiar face even then — and with more accuracy: 86%!

What will they test next?

They plan to test for other recognitions beyond just faces, Newport said.

Do fish only recognize human faces?

Humans use lots of devices to recognize people, including social cues. “Fish are not doing this,” Newport said. “For them, they are just looking for patterns.” That would answer the question whether Dory could find Nemo.

Finally, for the big one: Does my pet fish know me?


“There’s something like 30,000 species of fish. A blind fish is not going to be able to do this, sharks are fish and they can see color — so maybe,” Newport said.

Then she shared this observation.

When strangers walk into her lab, the fish “act skittish,” she said.

“When I walk in, they start spitting at me — many cases right in the eye.”

How’s that for accuracy?


Google’s new image-recognition program misfired badly this week by identifying two black people as gorillas, delivering a mortifying reminder that even the most intelligent machines still have lot to learn about human sensitivity.

The blunder surfaced in a smartphone screen shot posted online Sunday by a New York man on his Twitter account, @jackyalcine. The images showed the recently released Google Photos app had sorted a picture of two black people into a category labeled as “gorillas.”

The accountholder used a profanity while expressing his dismay about the app likening his friend to an ape, a comparison widely regarded as a racial slur when applied to a black person.

“We’re appalled and genuinely sorry that this happened,” Google spokeswoman Katie Watson said. “We are taking immediate action to prevent this type of result from appearing.”

A tweet to @jackyalcine requesting an interview hadn’t received a response several hours after it was sent Thursday.

Despite Google’s apology, the gaffe threatens to cast the Internet company in an unflattering light at a time when it and its Silicon Valley peers have already been fending off accusations of discriminatory hiring practices. Those perceptions have been fed by the composition of most technology companies’ workforces, which mostly consist of whites and Asians with a paltry few blacks and Hispanics sprinkled in.

The mix-up also surfaced amid rising U.S. racial tensions that have been fueled by recent police killings of blacks and last month’s murder of nine black churchgoers in Charleston, South Carolina.

Google’s error underscores the pitfalls of relying on machines to handle tedious tasks that people have typically handled in the past. In this case, the Google Photo app released in late May uses recognition software to analyze images in pictures to sort them into a variety of categories, including places, names, activities and animals.

When the app came out, Google executives warned it probably wouldn’t get everything right — a point that has now been hammered home. Besides mistaking humans for gorillas, the app also has been mocked for labeling some people as seals and some dogs as horses.

“There is still clearly a lot of work to do with automatic image labeling,” Watson conceded.

Some commentators in social media, though, wondered if the flaws in Google’s automatic-recognition software may have stemmed on its reliance on white and Asian engineers who might not be sensitive to labels that would offend black people. About 94 percent of Google’s technology workers are white or Asian and just 1 percent is black, according to the company’s latest diversity disclosures.

Google isn’t the only company still trying to work out the bugs in its image-recognition technology.

Shortly after Yahoo’s Flickr introduced an automated service for tagging photos in May, it fielded complaints about identifying black people as “apes” and “animals.” Flickr also mistakenly identified a Nazi concentration camp as a “jungle gym.”

Google reacted swiftly to the mess created by its machines, long before the media began writing about it.

Less than two hours after @jackyalcine posted his outrage over the gorilla label, one of Google’s top engineers had posted a response seeking access to his account to determine what went wrong. Yonatan Zunger, chief architect of Google’s social products, later tweeted: “Sheesh. High on my list of bugs you never want to see happen. Shudder.”

comdey club

One Barcelona comedy club is experimenting with using facial recognition technology to charge patrons by the laugh.

The comedy club, Teatreneu, partnered with the advertising firm The Cyranos McCann to implement the new technology after the government hiked taxes on theater tickets, according to a BBC report. In 2012, the Spanish government raised taxes on theatrical shows from 8 to 21 percent.

Cyranos McCann installed tablets on the back of each seat that used facial recognition tech to measure how much a person enjoyed the show by tracking when each patron laughed or smiled.

Each giggle costs approximately 30 Euro cents ($0.38). However, if a patron hits the 24 Euros mark, which is about 80 laughs, the rest of their laughs are free of charge.

There’s also a social element. Get this, at the end of the show the patron can also check their laughter account and share their info on social networks. The comedy club in conjunction with their advertising partner even created a mobile app to be used as a system of payment.

While law enforcement has been developing and using facial recognition technology for quite sometime, more industries are beginning to experiment with it.

Some retailers, for example, are considering using the technology to gauge how people might feel while shopping in a certain section of a store.

The U.K. company NEC IT Solutions is even working on technology that would help retailers to identify V.I.P patrons, such as celebrities or preferred customers.

According to a recent report on, the premium department store Harrod’s has been testing facial recognition during the last two years, albeit, the company has been primarily testing it for security reasons.

Facebook also uses facial recognition technology to suggest tags of people who are in images posted on its site.