CLOSE
Original image

Weird Camera Effects

Original image

We can never know the world around us as it really is; we can only know it as our brains perceive it. The process of interpreting the signals that come to our eyes is quite complicated, but it works well for us most of the time. Optical illusions occur when our minds interpret visual signals incorrectly. When we began to record images outside our brains, we added a mechanical layer of interpretation that can also go slightly wrong. Then we started using several different methods of recording visual images, and the possibility of incorrect interpretation multiplied, leaving us with some weird camera effects.

Google Earth Distortion

Artist Clement Valla posted a collection of distorted bridges gleaned from Google Earth. What happened here? Google Earth images are made from satellite pictures overlaid onto a 3D map of the terrain. The photographic images show bridges as they appear, but they don't fit over the terrain map, as they don't follow the terrain (if they did, they wouldn't be bridges). The software used to combine the photographs and the terrain map doesn't know the difference between a bridge and a road, and just lays the image down where the earth is.

Rolling Shutter Effect

Luke Mandle took this picture of his son with a digital camera. Notice that the child blinked when the picture was snapped. But... his reflection on the right of the picture show his eyes open! How did that happen?

A modern digital camera takes pictures by scanning from one side of the frame to the other (or top to bottom, depending on how you hold the camera). For most applications, that's fine. However, when objects move faster than the scanner, you get what is called the rolling shutter effect.

You see this same effect in a video of a moving propeller, taken with a scanning digital camera. The video below explains visually (and slowly) how the scanner cannot keep up with the speed of the propeller blades. Image by Flickr user Jason Mullins.

*

Even still scenes can be affected by the rolling shutter effect, if the movement is in the camera itself. If you want to do this on purpose, Wired has a tutorial.

This is an example of the rolling shutter effect done on purpose by moving the camera while shooting the picture. Image by Flickr user Matt Vinyl.

Stroboscopic Effect

You've noticed spoke-wheeled wagons in old films that appear to go backwards as the vehicle moves forward. When the movement of the wheel spoke (or in this case, propeller rotation) synchronizes with the frame rate, the rotation is seen as static, or moving in the other direction. This video was taken with a very short shutter speed, which kept the blades from blurring, and a frame rate that synchronized with the blade motion. Unless you can vary the frame rate while using the camera (which you can't), capturing this effect is purely by chance. Frame rates vary depending on the format, from 14 to 60 frames per second. A frame rate of 72 images per second is in the experimental phase. Converting motion pictures from one rate to another causes another set of problems.

The Moire Effect

A few days ago, I was watching a Three Stooges short from the 1930s. Larry Fine wore a striped shirt. The entire movie was in black and white, but Larry's shirt threw colors onto the TV screen like a prism. I've been told to never wear a striped shirt to a TV appearance, but there was no such restriction when filming with black and white analog film in the 1930s. Television is different. TV uses a raster scan, in which images are broadcast or relayed digitally by scanning lines from left to right and top to bottom. Each full scan is a frame of film or video. Movement in a striped pattern during a scan can cause a Moire effect, which you can manipulate on this page. The shirt you see was taken from a video illustrating the effect.

Encoding, recording, or broadcasting from one type of image capture to another can produce weird effects. Take an old movie recorded on analog film, or a TV show recorded with both color and black and white encoding, or encoded images from a different system (such as the European PAL system), and send it to a modern digital color TV, and you will see some weird effects, like the image above, which is an artifact of PAL decoding. As digital signals are more and more compressed to carry more information, there are trade offs in the ability to render older systems accurately.

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

Original image
quiz
arrow
Name the Author Based on the Character
May 23, 2017
Original image
SECTIONS
BIG QUESTIONS
BIG QUESTIONS
WEATHER WATCH
BE THE CHANGE
JOB SECRETS
QUIZZES
WORLD WAR 1
SMART SHOPPING
STONES, BONES, & WRECKS
#TBT
THE PRESIDENTS
WORDS
RETROBITUARIES