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5 Film Transitions worth Knowing

You see them every day, on TV shows, the news, movies, but how well do you know the most oft-used film transitions? Here are the big five:

1. The Dissolve

The dissolve is an editing technique where one clip seems to dissolve, or fade into the next. As the first clip is fading out, getting lighter and lighter, the second clip starts fading in, becoming more and more prominent. The process usually happens so subtly and so quickly, the viewer isn't even aware of the transition. A great example of this technique can be seen in Ransom's _flossy music video, Famous Last Words. Watch carefully at the very beginning: you'll see the camera pan up the façade of the apartment building (often called an establishing shot because it establishes the location of the action) and then dissolve into the next scene, where you see the cat owner saying "Here kitty, kitty."

2. The Wipe

This transition is the opposite of the dissolve in that it draws attention to itself. The best example of the wipe is what's known as the Iris Wipe, which you usually find in silent films, like Buster Keaton's or the Merrie Melodies cartoons—the circle getting smaller and smaller. Other wipe shapes include stars, diamonds, and the old turning clock.

The Star Wars films are chock-full of attention-grabbing wipes. Here are two good examples from The Empire Strikes Back. The first shows the clock wipe; the second, the diagonal wipe (pay no attention to the broken blocks at the start of the second clip--that's a technical glitch, not part of the film!):

3. The Cutaway

As the name implies, in the basic cutaway, the filmmaker is moving from the action to something else, and then coming back to the action. Cutaways are used to edit out boring shots (like people driving to their destination—why not see what the character is seeing or even thinking sometimes?) or add action to a sequence by changing the pace of the footage. My favorite use of the cutaway is in Family Guy where the technique is used to insert throwaway gags. Here's a great example:

4. The L Cut

The L Cut, also called a split edit, is a very cool technique whose name dates back to the old analog film days.

The audio track on a strip of celluloid film runs along the side, near the sprocket holes. In the L Cut transition, the editor traditionally cut the picture frames out of the strip, but left the narrow audio track intact, thus creating an L-shape out of the film. A different camera angle, or scene was then spliced into the spot where the old picture was, so the audio from the old footage was now cut over the new footage.

Of course, with digital editing, one doesn't need to physically cut anything anymore, but the transition is still widely used, and the name has remained the same.

There are many examples of this kind of cut in the following clip from the movie Quiz Show. Notice in the beginning how effective the L cut over to the dinner table is, allowing us to read Rob Morrow's expression. Split edits like these are especially effective in portraying conversations. Imagine how a simple conversation between two people might look if all we ever got was a ping-pong edit back and forth between the two people talking. The L cut allows the viewer to read the emotion on the listener's face, as the dialogue continues over.

Btw: if you're a real Quiz Show fan and haven't taken our Quiz Show quiz, fire this up and see how well you do.

5. The Fade

The fade in and fade out usually signal the beginning or end of a scene, especially if the filmmaker is fading to/from black. This is the most common, of course, but fading to white has become trendy, too. The opening title sequence from the HBO series Six Feet Under features many fades to black and a couple brief fades to white. The very last bit in the sequence fades slowly to white, and is my all-time favorite example of the transition.

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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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Name the Author Based on the Character
May 23, 2017
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