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Why Do We Get Red Eye in Photos?

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Grab a partner and look into his or her eye "“ or stare deeply into it, if appropriate "“ in a normally lit room. The quick and dirty version of how you're able to view each other is this: Light enters the eye through the cornea, the clear outer dome, and goes through the pupil. Then it travels to the cornea, which focuses it on the lens. The lens further focuses the light and spreads it across the retina. The retina receives the light and transmits signals via the optic nerve to the brain, which interprets the image.

As light enters the eye, some of gets reflected back, but the amount of light in most situations is so small, you wouldn't even know it. Right now, your partner's pupils look black and everything's normal. Now grab a camera and take a picture of your partner with the flash on. There's that demonic red eye.

Here's what happened: When you took the picture, the camera flash sent a lot of light into the eye in a very short time, the light reflected off the back of the eye and out through the pupil and, because the camera lens is close to the flash and able to capture images very quickly, it caught the light reflecting back out.

Seeing Red
So why is that light red?

Because the fundus, the interior surface of the eye that includes the retina, is loaded with melanin, a pigment that gives it a brownish-reddish color. Was that anti-climactic? Sorry.

Red eye is fairly easy to curb by using the "red eye reduction" setting found on most digital camera flashes. This setting causes the flash to go off once before the picture is taken, which causes the subject's pupils to contract and let less light in and out, and then another time to take the picture. Cameras with a flash farther away from the lens also reduce red eye because the flash hits the subject at a different angle than lens captures it.

Of course, red eye isn't all bad. The same mechanics of light reflection that ruin photos also allow doctors a non-invasive way to see inside the eye. Hermann von Helmholtz, a German physician, discovered in the 19th century that he could examine the retina by holding a bright light near his eye and shining it into patients' pupils.

If you've got a burning question that you'd like to see answered here, shoot me an email at flossymatt (at) gmail.com. Twitter users can also make nice with me and ask me questions there. Be sure to give me your name and location (and a link, if you want) so I can give you a little shout out.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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iStock
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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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