Extracting audio from visual information | Hacker News Reader

Extracting audio from visual information

newsoffice.mit.edu

573 pointsr0h1n127 comments

While it's cool to see this technique applied to consumer video, the general idea has been used in international espionage for a while now. In fact, Léon Theremin (yes, of the musical instrument) invented an early device capable of eavesdropping based on window vibrations: http://en.wikipedia.org/wiki/L%C3%A9on_Theremin#Espionage . I also recall that this is why all of the windows in the White House are fitted with tiny devices that vibrate the windows randomly as a countermeasure.

As a kid (in the early 80's!) I accidentally figured this out while "hacking" a sound based "walkie talkie" with a photo cell and a LED pointed at each other through a little telescope, from my house to my neighbors across the bock.

The device worked, but had a bug. a hummmm on the receiver.

For the longest time I could not figure out what was the "hummm", till I noticed it was there even with the transmitter off.. and then, I heard strange voices even with the transmitter being off!

Then I realized the humm was the reflection of incandescent light on the window, and the voices where the people in the room making the window vibrate too..

Ahh.. those where great fun days early on "hacker" life as a hacker. :)

>>till I noticed it was there even with the transmitter off.. and then, I heard strange voices even with the transmitter being off!

...and that is when little Johnny knew he had to lay off the shrooms.

I love hearing stories like yours though. I, too, miss the child-like wonder of making discoveries. We take the physical world we live in for granted, but there's just so much out there to see and learn from.

Well this system would in theory bypass the White House countermeasures

The technologies involved are quite different and this new approach radically simplifies the logistics.

Wouldn't it be really neat to apply this to HD movie sequences, and hear what the sounds on the set and the voices of actors were like pre-production? And how unreal some of the sounds must have turned out with all the visual tweaking that happens in production?

I had the exact same idea.

Why did I got down voted for that? It's true. Proof: http://www.crackajack.de/2014/08/04/visual-microphone-audio-...

Because posting "I had the exact same idea" without further interesting commentary is uninteresting.

I only down vote when something is demonstrably wrong or offensive. I thought that's how everyone is doing it, so I wondered what could I have written that was wrong or offensive?

Downvotes also apply to "demonstrably content-free".

BTW: not everyone uses exactly your own personal guidelines.

BTW: HN Guidelines include "Resist complaining about being downmodded. It never does any good, and it makes boring reading."

You missed the part where the video's frames per second has to be higher than the audio frequency.

You missed the part where they proved that this is not required.

When Hollywood isn't still using 24fps film cameras they're certainly not using consumer-grade camera sensors.

So maybe the only option would be The Hobbit?

The Hobbit still most likely doesn't use rolling shutter sensors, but I'm willing to be proven wrong.

Ah yes, that's probably true. I meant because of the higher frame rate.

I know a couple of Hollywood movies that were shot on consumer gear, eg http://www.usa.canon.com/app/html/HDV/XHA1/case_study_06.sht...

For this particular film the rather characteristic look of digital video is appropriate, whereas most productions would rather shoot with much fancier gear. But you'll find plenty DSLRs working on film sets these days, and you will see more and more convergence as high-quality sensors become a commodity. Black Magic have a pocket camera that delivers 13 stops of dynamic range.

It definitely has to be 2x the desired maximum frequency if you don't want aliasing. They probably capture higher frequencies by making assumptions about the input signal, but this will inevitably lead to aliasing when these assumptions are violated. The article doesn't really go into depth about precisely how they go about this.

They have lots of pixels, though, which means you should be able to go higher than nyquist with some clever work.

With two time samples you shouldn't be able to learn anything about the state of waves in a pool, but if each sample is a photograph with lots of pixels you can actually tell a lot.

High-speed camera or rolling shutter is required, (most) movies use neither.

You missed the part where 60 frames per second only allowed to identify the speaker and the number of people in the room.

> Because of a quirk in the design of most cameras’ sensors, the researchers were able to infer information about high-frequency vibrations even from video recorded at a standard 60 frames per second. While this audio reconstruction wasn’t as faithful as it was with the high-speed camera, it may still be good enough to identify the gender of a speaker in a room; the number of speakers; and even, given accurate enough information about the acoustic properties of speakers’ voices, their identities.

If you watch the video in the post, the demo is surprisingly accurate.

The demo in the video is based on a high-speed (1000+fps) recording by a special camera, not on 'normal' video.

Some cheap video cameras don't shutter the frames (grabbing all pixels at once), they progress thru pixels - leading to a usually-annoying stretchy visual effect. If the sound affects much of the frame with suitable uniformity, you've turned a 60fps camera into a 2MHz "visual" audio sampler (lots of noise, artifacts, & other difficulties aside).

Like in this clip, taken with an iPhone, of guitar strings vibrating?

http://youtu.be/TKF6nFzpHBU?t=10s

Exactly. And the term I was looking for is "rolling shutter" (a confident term for an inaction).

I would expect that you need to acquire the raw footage; post processing (and compression) will ruin the data.

I record the dialog for your movies. Aprt from obvious sound effects like Darth Vader voices or so, actors' dialog is changed as little as possible during post production. It's not heavily EQed or comrpessed, because that would mean a corresponding change to the room tone and background noise, which would then fluctuate unnaturally as you went back and forth between the participants in a scene. In scenes with a lot of movement actors' voices sometimes sound a little deeper than in real life, because they are fitted with a tiny wireless microphone, and there's usually some resonance from the chest cavity.

But generally what you hear is very close to how the person actually sounds - although their accent or inflections may be adopted for the purposes of their role. This can be a bit jarring; I've worked with method actors who maintain their screen accent at all times during production until the film is done, so when they switch back to their regular accent after a month or so it's extremely disorienting, since I've been listening to them in my headphones day in day out for weeks, and am paid to pay as much attention to their voices as the cinematographer pays to their faces.

Some actors go even farther in support of their public image. Rock Hudson had a somewhat high voice that producers deemed incompatible with his looks, so during production he would warm up every day by shouting for 20 minutes and gargling with orange juice to inflame his vocal cords, and of course he smoked a lot too. What actors will do to themselves in pursuit of screen presence far exceeds anything I've ever been asked to do in post. Editing dialog is more than enough work without trying to sculpt people's voices.

Thanks a lot for that insight. I will assume you work primarily for Hollywood with that description. It is interesting to hear about the behind-the-scenes from film industries in different parts of the world.

In the Indian film industry (maybe not so much Bollywood, but more of the local ones like Tamil, Malayalam, etc) there's a LOT more post being done. Some entire Malayalam films have dubbed voices (for the original movie). Not to mention nearly every song track does not have the singing recorded during the shooting of the dance sequences. So those sets and actor voices I would bet would be completely different.

Italian films from the 70's used to overdub all the vocals, and of course it wasn't exactly in sync so it looked terrible.

Yeah, here in California we have the luxury to do good production sound almost all the time. Dubbing the voices later all sounds very different, because the recordings are not in the same space as the original production and so on. I forgot to think about that aspect, because here we always record production sound unless there is an impossibly high level of noise (eg from a wind machine or something). With modern cameras it's been very good for the sound department because they are so quiet, whereas older 16 and 35mm film cameras were quite noisy, like a sewing machine, and it required some work to prevent this messing up the dialog recording.

Reminds me a little of "Dual Photography" as presented at Siggraph in 2005. All the data you need to construct a new view is available if you know where and how to look: https://www.youtube.com/watch?v=p5_tpq5ejFQ

Hah! I have the book that is used in the example picture. Though, I suppose everyone who studied CG in the early to mid 2000s has that book.

Incredible and terrifying at the same time. If they're doing this kind of stuff right now with consumer cameras, imagine how effective this technology will be in just a few decades. Privacy is fading quickly with the advent of exciting technology like this.

you need a camera that captures at least 2,000 frames per second.

They also took advantage of rolling-shutter sensors running at conventional frame rates to get a "murky" audio signal.

> Because of a quirk in the design of most cameras’ sensors, the researchers were able to infer information about high-frequency vibrations even from video recorded at a standard 60 frames per second.

The audio from the 60fps video sounds pretty bad though, which I suspect is mostly because of inherent maths/physics limitations rather than anything that software can improve.

Edit: They mention capturing frequencies up to five times higher than the 60Hz frame rate, which would mean a maximum frequency of 300Hz, which would suggest the equivalent of 0.6kHz audio, which is a 73.5th of the audio rate of a CD. I doubt you'd get intelligible speech from current consumer hardware using this technique.

There is some small possibility of improvement through software techniques, such as maybe data assimilation, which can use information from surrounding time-frames to improve the measurement. This is assuming that the magnitude of vibrations changes a lot slower than the vibrations themselves, which is usually true, and how most audio compression works. It may be able to clean up the sound a little. However, I would say that the results they have obtained so far are very impressive.

The data comes in faster than 60 fps. A camera sensor doesn't capture the entire frame instantly every 1/60 second. It progressively scans through the frame over some measurable fraction of that 1/60 second. This is that quirk.

Suppose the camera scans 720 lines in HD every 1/60 second. Each row is offset in time by 1/43200 second. A rigid object could be slightly offset in space on each line of pixels, indicating that sound waves perturbed it in the time gap between when the camera captured each line. So that subframe video data can be turned back into audio at a much higher frequency than that apparent 60 Hz video sampling rate.

In other words, we're not just talking about 60 frames-per-second from a camera. It's really perhaps 43,200 rows per second, an enormously higher sampling frequency.

Well the reader would read as fast as it can.

Let's say that it would read the entire image in 1/120 second, then it is waiting and does nothing another 1/120 second before it starts reading next frame.

The real number would be significantly smaller. Therefore they can not bump the sample rate more then five or six times. And I imagine they are using some intelligent algorithm to evenly space out the captured samples already.

> The data comes in faster than 60 fps

Yes, yes, that was completely obvious from the article. We are getting thousands of "measurements" per second.

However, each of those measurements is incredibly inaccurate. Each one is trying to detect the change of colour of 1/200 of the colour range in a single pixel. You may be getting less than a single bit of entropy per measurement.

An advanced signal processing technique will look at the longer-term picture. Sound vibrations are not a random walk - they tend to be a combination of sine wave vibrations, where the rate of change of magnitude of each wavelength is significantly lower than the vibrations themselves. Therefore they are to a certain extent predictable, and this predictability is used by audio compression algorithms. The signal processing algorithm will have to make use of the extremely limited information coming from the measurements, and match up possible sets of varying sine waves that could be causing those measurements. This may be sufficient to reject some of the noise that we could hear on that video, and clean up the sound a bit, but it is quite a hard (and CPU-intensive) processing task.

"intelligible speech", are you sure that speech recognition really requires whole frequency range? Often it seems that data can be extracted after all, even if most of it is missing.

A CD has a lot of overkill for basic speech. Doing a test here with some speech samples, 2kHz is ugly but intelligible, 1kHz is a mess but mostly understandable with effort, and 600Hz is almost useless for trying to find words (without any practice or computer assistance, of course).

It's reminiscent of the laser microphone, which measures sound-induced vibrations in objects by bouncing a laser off them, and reconstructs the original sound waves

http://en.wikipedia.org/wiki/Laser_microphone

or active and passive sonar in their difference.

This is amazing. Imagine taking high definition video of a crowd of people. You could pick out objects nearby and hear what individuals are saying. You could nearly produce a 3D auditorium by sampling different points in a video. Couple this with a 3D camera and an Oculus Rift, you could have something incredible.

While I'm not sure how closely this matches up, it sounds like you may at least be interested in exploring these concepts:

http://en.wikipedia.org/wiki/Cocktail_party_effect

http://en.wikipedia.org/wiki/Independent_component_analysis

Edit: Spacing.

Reminds me of this great hoax / video piece from a few years ago about French scientists decoding voices that were accidentally encoded into vases in ancient Pompeii

http://www.youtube.com/watch?v=ZbpwBTDvXrI

It's in French, but this makes it even funnier.

  Because of a quirk in the design of most cameras’ sensors,
  the researchers were able to infer information about
  high-frequency vibrations even from video recorded at a
  standard 60 frames per second.

Can anyone explain what this quirk is?

It's explained further on in the press release. The "quirk" is the same one that causes rolling shutter artifacts in videos: reading the camera's sensor one row at a time, instead of all at once.

Cameras basically read their sensors one row of pixels at a time. By measuring the distortion of each row, they can detect vibrations higher than the camera's frame rate.

So it's like if 960-row video at 60fps were actually a 57600 rows-per-second video, right? Which they can extract info from because having more rows in a still frame doesn't mean having more information (at least not linearly), i.e. in still frames with no rolling shutter, rows contain redundant vibration already extracted from previous rows.

So having a rolling shutter is good for this specific application because it trades off resolution (most of which is redundant or insignificant information) for sampling rate.

Between the time the first and last row are read, the object might've moved a little bit. So if you take a picture with your phone from the side window of a moving car, the picture will appear stretched.

Sure, I meant it specifically as a guess of how it's applied to sound extraction and how it means you have ROW samples per frame.

What's at play is the sampling theorem. Using instantaneous shutter, considering the speed of sound is very high*, every part of the image is resonating essentially the same sound; the sampling theorem says you can only perfectly reconstruct up to F/2 hertz if you sample at F frames per second. The rolling shutter introduces regular variations at at much higher frequency, allowing much better sampling.

- Actually, doing a quick calculation shows that at 1khz a 1/2 wavelength is just 17cm. I wonder how precise spatial scene/source information has to be to allow this diversity to contribute significantly to the sampling. If you had a planar source and precisely spaced two objects it shouldn't be too hard to increase spectral resolution. The complementary possibilities are also be interesting -- with precisely laid out N objects and a good spectral resolution for each afforded by the shutter you could perhaps resolve the sound into N distinct sources, allowing to determine the origin of the sound; with precisely known source locations you may be able to extract some object location information.

Rolling shutter effect. http://en.wikipedia.org/wiki/Rolling_shutter

And now think of how much high definition video, CCTV, and other forms of recordings already exist.. and then think about running large collections of pre-existing video through such algorithms, along with the best speech-to-text in the business. You could have a whole new Wikileaks on your hands :-)

Thankfully most CCTVs are so crappy and so low framerate, I doubt they can get much out of it.

If you want to record a particular person through a window, for instance, you can get a laser microphone that catches the vibrations of the glass.

Yeah, I've heard that's what the spies use, although that does require specific effort. What I find more intriguing about this development is how pre-existing footage could be used. While HD CCTV is certainly not popular, I suspect enough has been said in the presence of existing HD video to incriminate a few people :-)

I think it unlikely that pre-existing footage can be used, because HD video is almost always compressed, thus masking the minute vibrations in the pixels. The algorithm described in the article work best for uncompressed video directly from the image sensor, and they can run it in real-time without needing to store the video.

You'd be better off learning to lip read.

This is from the movie Eagle Eye, right? The evil computer watches the vibrations in a cup of coffee while someone is speaking.

The first thought to cross my mind.

They also did something like this in the recent remake of "Robocop". Some thugs are in a diner having a discussion, and it's caught on CCTV. Later, the main character goes back and analyzes the video and extracts the audio from it, presumably based on some vibrations somewhere in the scene. They don't say, but I got the impression it was from the window vibrations, similar to the technique of shooting a laser at it and watching the vibrations of the reflected light.

lol that is the first thing that I thought as well. I just passed it off as a typical Hollywood trope, but now I'm quite delighted to see it become a reality.

> I just passed it off as a typical Hollywood trope

I often wonder what makes people to pass off things like that as "typical tropes", where they are obviously realistic and doable.

"Any sufficiently advanced technology is indistinguishable from magic." Those who view it as magic will express it as a trope, even if it is merely advanced technology.

Just yesterday I chuckled when recalling a James Bond movie involving Bond driving a car in reverse by viewing a back-up camera. At the time, it formed an instant "trope" because it was so cool and novel. Yesterday, I was doing exactly that with the backup camera on my car - obviously realistic and doable technology.

This is a beautiful hack in best tradition of the term.

If only I hadn't been wearing my tinfoil hat, they'd never have known my plans!

The first thing I thought of: a story called "The Extractor" that recently featured on The Truth podcast: http://thetruthpodcast.com/Story/Entries/2014/3/9_The_Extrac...

Reminds me of Alvin Lucier's "I am sitting in a room" audio experiment.

The watery sounds you find when listening to low bit-rate mp3, there was a bit of that in the video, especially the "Mary had a little lamb..." skit.

From watching the video, I get the impression that there is a very large amplitude of the input audio -- taking advantage of the "loud" in loudspeaker.

A good question. I too got that impression from the first example. In the second example (chips bag through glass), the "control" audio had a lot of reverb, which might have been introduced by the phone they acquired it through, but may also suggest that it wasn't just a person talking, but a reproduction through some kind of amplification equipment.

A loudspeaker is a term for a speaker that you traditionally think of when you think of a speaker: https://en.wikipedia.org/wiki/Loudspeaker

If this is something that commodity hardware is now capable of, a total surveillance society is now very cost-effective.

Is the stability required from the camera a dealbreaker when it comes to outdoor mounted cameras in moving air, or would it be pretty easy to algorithmically filter that out? i.e. are winds and drafts predictable enough that they could be removed accurately enough for smaller vibrations to remain?

Wait, so what would be the best reflector for this type of thing? If I could host the ultimate cocktail party, placing ferns/etc all around the room, could I record every conversation with a single camera?

What would those ferns look like? What would they be made of? I'm imagining christmas trees made of cellophane fibers or something.

If you're allowed to place the ferns, why not simply hide microphones in them?

Because microphones can be detected. When ferns are detected, they are assumed to be innocuous.

I don't know, you may be very far away. The camera could be in space, or maybe on a plane. I mean, if you can hide microphones, the ferns would be irrelevant anyways, apart from being a good distraction.

Kind of off topic but just last night I was watching some (silent) lightning in the clouds, thinking how much more localized sound energy is when compared to light. In other words, I can see for light-years but can't hear much anything 100ft away. Or perhaps it's just our sensors are more sensitive to light waves than air pressure waves. Now I realize sound isn't so localized! It leaks. /rant

Reminds me of the technique used to uncover "invisible" motion by amplifying the tiny movements found in a video: http://bits.blogs.nytimes.com/2013/02/27/scientists-uncover-...

It doesn't seem to mention what kind of camera you'd need to do this at the mentioned distance (15 feet). I'm assuming it's at least a couple thousand bucks, or maybe even so expensive that most professional photographers won't have it, but does anyone actually know? Or did I miss it in the article?

it says about the frame rate necessary, we can only infer the price of the camera.

The video goes into a bit more detail and shows a couple of things that address your question.

1) A lot of the tests were done with a camera that costs thousands of dollars. You can see images of the camera used in one of the experiments.

2) They were able to use consumer-grade cameras to also capture sound. Even frequencies up to 5x higher than the actual 60 FPS of the captured video.

I wonder how well a GoPro would do? They can do 120fps at 720p or 240fps at WVGA.

Not very well, at least for the initial approach with a high-speed camera. With 240 fps you're limited to 240 samples per second. If I'm not terribly mistaken that would limit you to frequencies up to 120 Hz in the reconstruction.

But the GoPro has a rolling shutter as well, so their second approach would be applicable. However, that effectively relies on rows per second and while you have a higher frame rate you have a lower resolution. In the end they could cancel each other out.

I think this is the cheapest (relatively speaking) high-speed camera: http://edgertronic.com/

There are also some consumer cameras that can capture almost 1,000 fps from a small sensor window. I wonder if those would work.

The paper says they used a Phantom V10. I'm not knowledgeable about such devices, but various Google results suggest such a camera might top $100,000 depending on the mounts, lenses, and accessories (e.g. data storage and transfer equipment).

Reminds me of how deaf people can "listen" to music with a sheet of paper or a balloon in their hands.

*deaf people ;)

Either way it's a superpower.

damn it! lol

While a different technique, this reminds me of how researchers were able to extract keystrokes based on the sound from each key press.

Here is the original paper:

http://rakesh.agrawal-family.com/papers/ssp04kba.pdf

Also reminds me of this: http://cnx.org/content/m13224/latest/?collection=col10380/la...

How much vibration does sound actually cause an object. I tried humming near various objects and noticed nothing. I used to be really interested in early mechanical microphones and sound recording, but I couldn't find much information on how they work either.

Gently put your fingers on a (cheap) speaker cone and then play back some music.

Your eyes wouldn't be able to see a 2000 Hz vibration, most vibrations that we perceive as sounds (except from the very low vibrations) are so fast that even with a huge amplitude they'd be just a motion blur for our eyes.

Now, a 2000 fps camera can see things that a naked eye can not.

But I should see a blur or something, unless it happens to be vibrating at exactly the frame rate of both of my eyes (and even that would cause some weird effects, see helicopter blades spinning.)

Almost missed your comment btw.

Reminds me of the attempts to extract audio from the groves on ancient spun pots:

http://en.wikipedia.org/wiki/Archaeoacoustics#Past_interpret...

Am I the only one who isn't getting any audio from the video at all? I tried in two different browsers, downloaded the video with youtube-dl and tried to play it with mpv, everything to no avail, it's just a video with no sound.

Pretty ironic ... I wonder if they could run their algorithm on the video on their page ...

You probably only downloaded the DASH video, this should work:

$ youtube-dl -f 18 http://newsoffice.mit.edu/2014/algorithm-recovers-speech-fro...

You can use the -F option to list the available formats.

Try noise cancellation on it. And results may be more clear. I did a project on active noise cancellation using neural networks. It should apply here as well.

They did already, by the sound of the audio.

Now I am gonna be suspicious of chip bags and plants everywhere. We will need to invent telepathic communication (mind to mind) to preserve privacy.

> We will need to invent telepathic communication (mind to mind) to preserve privacy.

Or maybe it's time to think how to adapt to a world without privacy?

This is fun research, but it's basically just a microphone (which works by turning these vibrations into magnetic pulses that generate electric pulses) using a much, much more complex signal processing mechanism (observing photons bouncing off the vibrating surface, translating the digital representation of those photons into a digital simulation of the electric pulses a microphone would generate, and turning that digital simulation into real electric pulses).

This algorithm is really incredible, I can only imagine the improvements to this in 20 years

Binoculars as bugging devices...

I am just worried that they are picking up part of information from camera mic. Maybe camera mic output is not totally independent from the video sensor, and is encoded in the final video.

They put the camera behind soundproof glass for one of their tests.

I know, but I still wonder about level of soundproof/mechanical vibration and the level of mic and camera sensor isolation VS level of optical vibration. In addition sound can travel many different paths since it is mechanical vibration, and traveling through sound proof glass is not the only path. Anw cool project.

I'm sure it's such a tiny amount that it isn't really relevant. Easy enough to test. Remove the bag of chips and just film the floor. See how much signal you can derive from that. Not exactly perfect science but gives a quick indication of "signal" that's reaching the system via other means.

Actually, what I think would be even better would be to record the bag of chips through the window, but play the sound outside where the camera is.

The subtitle of the article is "Algorithm recovers speech from the vibrations of a potato-chip bag filmed through soundproof glass."

The camera used in most of these experiments (a Phantom high speed camera) doesn't even have a microphone - so that would be quite impossible.

Thanks. However, there is still a possibility that mechanical vibration is coming to the video sensor through some path (floor+camera tripod), and affecting the video. After all mechanical vibration is affecting the potato chips. Why is it so impossible to affect video sensor? Especially in the sensitive high speed camera? Let the downvotes begin :)

I fail to see how that would make this any less impressive.

If my evil :) speculation is true, the camera sensor is just picking up mechanical vibrations from environment (coming through air, tripod etc.) and encoding them into video. There is no proof that the bag of chips is vibrating (they even say that the vibrations are not visible on footage). They are extracting something from video, but that something may just be spuriuos pickups by equipment, and not related image/video of bag of chips. Thus it would be just a silly way to measure spurious mechanical vibrations.

Well, the chip bag weighs a few grams at most. The camera and gear weigh something like 50kg. The higher the video frame rate, the greater the damping you need to prevent unwanted vibration. Notice the tests were performed with a speaker playing back inside the room rather than a person, in order to minimize mechanical vibrations. The sensors are very firmly mounted inside the camera, trust me.

I am amazed this wasn't funded by DARPA.

I would bet money that this technique is already well known and has been used by certain intelligence agencies.

I think this will be a good help for visually challenged people. I wish to see if this goes in that direction.

Can somebody executive summary this big lump of wooly garbage?

TL;DR - sound is a physical phenomenon, pushing on objects (more pronounced on wide thin lightweight things like bags). A fast enough video camera with image enhancement can "see" the sound affecting the object, which then can be translated to recreating the sound from the video image.

Not long ago there was a spate of HN articles about apps that could measure your heart rate via the camera (it watches for & measures subtle changes in your skin color which occur during the pulse cycle). This is exactly the same idea, just with a much faster "pulse".

I expect the researchers will next discover the "rolling shutter" (a "that's not a bug, it's a feature!" of cell phone cameras) and discover how to extract the audio info without the need for high-framerate cameras. atomatica found a perfect example: http://youtu.be/TKF6nFzpHBU?t=10s

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