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Scientists Say We Could Be Fooled by Clark Kent’s Glasses

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YouTube // flashback fm

Ready to feel a little silly? Researchers have found that wearing glasses actually does make unfamiliar faces harder to identify, which means that Clark Kent could conceivably get away with his ridiculous disguise. The results were published in the journal Applied Cognitive Psychology. 

Lead author Robin Kramer is a psychology researcher at the University of York. He says exploring the success of Superman’s flimsy costume is meaningful not only for comic book readers, but for international security. After all, photo IDs are only as good as the ability of law enforcement and other security officials to match a person’s face with the photo on their passport or driver’s license. 

Previous studies have shown (and common sense suggests) that we’re better at spotting disguises when they’re worn by people we know. But when it comes to strangers, it doesn’t seem to take much to throw us off. 

Kramer and his York colleague Kay Ritchie, a facial-recognition expert, decided to test just how easily we and the citizens of Metropolis could be fooled. They brought volunteers into the lab and showed them a series of pairs of candid photos of the type you might see on Facebook. Some pairs of photos depicted the same person, while others showed two people who looked somewhat similar. In some of the pairs, both people wore glasses. In others, neither wore glasses. The remaining pairs included one photo with glasses and one without.

Sure enough, simply adding glasses to one person’s face was enough to throw the study participants for a loop. When both photo subjects in a pair were either bespectacled or bare-faced, people were able to tell if they were the same person with about 80 percent accuracy. But once the researchers added glasses to one photo, the participants’ success rate dropped by 6 percent—not a huge dip, but statistically significant, the authors say. Clark Kent and Superman did indeed look more like two different people.

Kramer and Ritchie note that Clark Kent's camouflage would likely only work on strangers. It definitely wouldn’t have fooled Lois Lane, who has, shall we say, probably seen him with his glasses off. But the countless beneficiaries of Superman’s heroics could easily have overlooked the difference between the Man of Steel and his bookish alter ego. 

The researchers say these findings could help inform real-life crime fighting. "We hope that this research can be used by legal authorities to help inform future policies on identification for security purposes," Kramer said in a press statement, "particularly in the UK, where individuals who normally wear glasses are required to remove them for their identification cards."

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]