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Snapchat World Lenses Are the Next Step in Augmented Reality

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Snapchat

Since it was founded in 2011, Snapchat has used cutting-edge technology to successfully set itself apart from other photo-sharing services. The app's latest feature, Snapchat World Lenses, integrates colorful, 3D objects into real-world scenes captured on your smartphone.

As The Verge reports, Snapchat World Lenses were introduced on Monday, April 18. This is the latest experiment with augmented reality we’ve seen from the mobile app. As Snapchat says in a statement:

"We launched Lenses over a year ago as a whole new way to express ourselves on Snapchat. Since then, we've become puppies, puked rainbows, face-swapped with our best friends—and begun to explore how Lenses can change the world around us.

Today, we’re adding new ways to use Lenses."

Unlike most of the app's high-tech filters, Snapchat World Lenses aren’t designed for faces. They’re meant to be plopped down anywhere in the space being recorded on your phone’s rear-facing camera. That’s where the augmented reality element comes in: The 3D objects behave as if they’re physically in front of you. Move your camera closer and the animation grows bigger; pull it away and the objects shrink, appearing more distant.

The introductory animations, which can be accessed through Snapchat’s lenses deck, include a cartoon rainbow, a crying cloud, sprouting flowers, and a colorful “OMG” written in bubble letters. The feature will be updated with new lenses on a daily basis. You can watch a demonstration of Snapchat World Lenses in the video below.

While the technology may look futuristic, it’s not exactly new. In 2015, Microsoft introduced the HoloLens, an augmented reality visor that allows wearers to view 3D versions of their favorite apps and games (like Minecraft) as part of the physical space around them. But with a $3000 price tag, the headset wasn’t the ideal vehicle for delivering augmented reality to the masses.

That distinction belongs to Pokemon Go. Last summer, the mobile game brought 3D characters into the real world by way of smartphone cameras. Since the world reached peak Pokemon Go mania shortly after its debut, no other 3D augmented reality app has come close to matching its popularity.

Now that Snapchat is embracing similar technology, users shouldn’t be surprised to see other social media sites launching their own versions of the 3D lenses. Facebook has been known to take direct inspiration from features that originated with Snapchat (like filters and stories), and we already know that Facebook has experimented with virtual reality in the past. Download or update Snapchat today to judge the potential impact of World Lenses for yourself.

[h/t The Verge]

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iStock // Ekaterina Minaeva
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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
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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]

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