In an earlier video they made a couple years back about Disney's sodium vapor technique Paul Debevec suggested he was considering creating a dataset using a similar premise: filming enough perfectly masked references to be able to train models to achieve better keying. So it was interesting seeing Corridor tackle this by instead using synthetic data.
With regards to the sodium vapor process, an idea has been percolating in the back of my head ever since I saw that video. But I don't really have the budget to try it out.
theory: make the mask out of non-visable light
illuminate the backing screen in near Infra-Red light. (after a bit of thought I chose near-IR as opposed to near-UV for hopefully obvious reasons)
point two cameras at a splitting prism with a near IR pass filter(I have confirmed that such thing exists and is commercially available)
Leave the 90 degree(unaltered path) camera untouched, this is the visible camera.
Remove the IR filter from the 180 degree(filter path) camera, this is the mask camera.
Now you get a perfect non-color shifting mask(in theory), The splitting prism would hurt light intake. It might be worth it to try putting the cameras really close together , pointed same direction, no prism, and see if that is close enough.
This approach was used in the 1950s/60s with ultraviolet light (rather than IR) to create a traveling matte. I'm not sure why visible-light techniques won out. Easier to make sure that the illumination is set up correctly, maybe?
That is far-IR, thermal stuff, Near-IR, 700 nanometer-ish is right below red in human vision.
Camera sensors can pick up a little near-IR so they have have a filter to block it. If that filter was removed and a filter to block visable light was used in place you would have a camera that can only see non-visable light. Poorly, the camera was not engineered to operate in this bandwidth, but it might be good enough for a mask. A mask that does not interfere with any visible colors.
I'll do you one better, which requires no special cameras (most have IR filters) nor double cameras or prisms.
Shoot the scene in 48 or 96 fps. Sync the set lighting to odd frames. Every odd frame, the set lights are on. Every even frame, set lights are off.
For the backing screen, do the reverse. Even frames, the backing screen is on. Odd frames, backing screen is off.
There you go. Mask / normal shot / Mask normal shot / Mask ... you get the idea.
Of course, motion will cause normal image and mask go out of sync, but I bet that can be remedied by interpolating a new frame between every mask frame. Plus, when you mix it down to 24fps you can introduce as much motion blur and shutter angle "emulation" as you want.
From ~04:10 till 05:00 they talk about sodium-vapor lights and how Disney has the exclusive rights to use it. From what I read the knowledge on how to make them is a trade secret, so it's not patented. Seems weird that it would be hard to recreate something from the 1950's.
I also wonder how many hours were wasted by people who had to use inferior technology because Disney kept it secret. Cutting out animals and objects from the background 1 frame at a time seems so mindnumbingly boring.
The lights are relatively easy to get. iirc (it's been a bit since I watched their full video on the subject[1]) the hard part to find was the splitter that sends the sodium-vapor light to one camera and everything else to another camera.
Yeah, that's just nonsense. We used sodium vapor monochromatic bulbs in my high school physics class to duplicate the double slit experiment.
I suspect the real reason is that digital green screen in the hands of experienced people is "good enough" vs the complication of needing a double camera and beam splitting prism rig and such.
The community has managed to drastically lower hardware requirements, but so far I think only Nvidia cards are supported, so as an AMD owner I'm still missing out :(
The idea behind a greenscreen is that you can make that green colour transparent in the frames of footage allowing you to blend that with some other background or other layered footage. This has issues like not always having a uniform colour, difficulty with things like hair, and lighting affecting some edges. These have to be manually cleaned up frame-by-frame, which takes a lot of time that is mostly busy work.
An alternative approach (such as that used by the sodium lighting on Mary Poppins) is that you create two images per frame -- the core image and a mask. The mask is a black and white image where the white pixels are the pixels to keep and the black pixels the ones to discard. Shades of gray indicate blended pixels.
For the mask approach you are filming a perfect alpha channel to apply to the footage that doesn't have the issues of greenscreen. The problem is that this requires specialist, licensed equipment and perfect filming conditions.
The new approach is to take advantage of image/video models to train a model that can produce the alpha channel mask for a given frame (and thus an entire recording) when just given greenscreen footage.
The use of CGI in the training data allows the input image and mask to be perfect without having to spend hundreds of hours creating that data. It's also easier to modify and create variations to test different cases such as reflective or soft edges.
Thus, you have the greenscreen input footage, the expected processed output and alpha channel mask. You can then apply traditional neural net training techniques on the data using the expected image/alpha channel as the target. For example, you can compute the difference on each of the alpha channel output neurons from the expected result, then apply backpropagation to compute the differences through the neural network, and then nudge the neuron weights in the computed gradient direction. Repeat that process across a distribution of the test images over multiple passes until the network no longer changes significantly between passes.
I'm a software engineer that, like the vast majority of you, uses AI/agents in my workflow every day. That being said, I have to admit that it feels a little weird to hear someone who does not write code say that they built something, without even mentioning that they had an agent build it (unless I missed that).
theory: make the mask out of non-visable light
illuminate the backing screen in near Infra-Red light. (after a bit of thought I chose near-IR as opposed to near-UV for hopefully obvious reasons)
point two cameras at a splitting prism with a near IR pass filter(I have confirmed that such thing exists and is commercially available)
Leave the 90 degree(unaltered path) camera untouched, this is the visible camera.
Remove the IR filter from the 180 degree(filter path) camera, this is the mask camera.
Now you get a perfect non-color shifting mask(in theory), The splitting prism would hurt light intake. It might be worth it to try putting the cameras really close together , pointed same direction, no prism, and see if that is close enough.
Camera sensors can pick up a little near-IR so they have have a filter to block it. If that filter was removed and a filter to block visable light was used in place you would have a camera that can only see non-visable light. Poorly, the camera was not engineered to operate in this bandwidth, but it might be good enough for a mask. A mask that does not interfere with any visible colors.
Shoot the scene in 48 or 96 fps. Sync the set lighting to odd frames. Every odd frame, the set lights are on. Every even frame, set lights are off.
For the backing screen, do the reverse. Even frames, the backing screen is on. Odd frames, backing screen is off.
There you go. Mask / normal shot / Mask normal shot / Mask ... you get the idea.
Of course, motion will cause normal image and mask go out of sync, but I bet that can be remedied by interpolating a new frame between every mask frame. Plus, when you mix it down to 24fps you can introduce as much motion blur and shutter angle "emulation" as you want.
I also wonder how many hours were wasted by people who had to use inferior technology because Disney kept it secret. Cutting out animals and objects from the background 1 frame at a time seems so mindnumbingly boring.
1. https://www.youtube.com/watch?v=UQuIVsNzqDk
I suspect the real reason is that digital green screen in the hands of experienced people is "good enough" vs the complication of needing a double camera and beam splitting prism rig and such.
https://www.youtube.com/watch?v=abNygtFqYR8
An alternative approach (such as that used by the sodium lighting on Mary Poppins) is that you create two images per frame -- the core image and a mask. The mask is a black and white image where the white pixels are the pixels to keep and the black pixels the ones to discard. Shades of gray indicate blended pixels.
For the mask approach you are filming a perfect alpha channel to apply to the footage that doesn't have the issues of greenscreen. The problem is that this requires specialist, licensed equipment and perfect filming conditions.
The new approach is to take advantage of image/video models to train a model that can produce the alpha channel mask for a given frame (and thus an entire recording) when just given greenscreen footage.
The use of CGI in the training data allows the input image and mask to be perfect without having to spend hundreds of hours creating that data. It's also easier to modify and create variations to test different cases such as reflective or soft edges.
Thus, you have the greenscreen input footage, the expected processed output and alpha channel mask. You can then apply traditional neural net training techniques on the data using the expected image/alpha channel as the target. For example, you can compute the difference on each of the alpha channel output neurons from the expected result, then apply backpropagation to compute the differences through the neural network, and then nudge the neuron weights in the computed gradient direction. Repeat that process across a distribution of the test images over multiple passes until the network no longer changes significantly between passes.
Still Python unfortunately.