Show HN: Simple algorithm and color space to generate diverse skin tones (toneyalexander.github.io)

627 points by automatoney ↗ HN
Hello HN!

I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy.

I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has.

The methodology might be a bit shaky, but hopefully the result is as helpful for others as I have found it! There's lots of room for improvements (see the Future Work section), but I'm really happy with how it turned out.

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This is super cool! I have always loved projects that try to categorize color space. Usually my work has gone in the other direction - isGray, isCloseToWhite, isPastel - but it's the same insofar as it's defining shapes like your matplot visual.

Wish I had this on hand like this three or four years ago when I was working on VR avatar software - we had hard-coded skin tone options at the time - would have been a cool addition!

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...Did you read the article, or use the picker? It's a continuous (up to the limits of RGB quantization) space which includes thousands upon thousands of shades of black. The selected tones at the top of the article are random and change continuously.
Nice. Most of these colors look right to me, but I'm also seeing green, blue and purple? If you're curating colors from the space manually then it's not a problem.

"Only realistic colors" would be a different problem. And I'm not sure if there's a way to solve that problem without excluding some real colors too.

(Maybe if the colour selector was a different shape? I don't know much about color spaces.)

Yes absolutely right on - I mention much deeper in the page that in a picker UI you can use a bigger range, but that in a generation context you might want to be a bit more selective. I go into it a bit more when I explain what R^2 is.

"not sure if there's a way to solve that problem without excluding some real colors too" - 100% right on that too. A big part of this work was to define a way to tweak/improve the equations in order to approach a solution to these issues - part of my hope in sharing is to get more eyes and brains thinking about this and proposing improvements!

If you drag the bottom slider all the way to the right you only have plausible skin tones. Drag it all the way to the right and you can match skin tones for orcs, Na'vi and djinn
Reducing the R^2 value to ~1.5 excludes skin colors that are extremely blue, green and purple. That seems to be a happy medium between including real outliers and excluding colors like green.
Seems to underrepresent pale skin tone variety
yeah, skin tone variations often feels it's about limiting lighter tone options while adding luminosity options for the exact same brown color. There seem to be B channel differences across darker colored people, and I wouldn't be sure if they are better represented either.
This is beautiful work! First, I thought this would involve using PCA to go from 3D to 2D, which would result in an easier selector to use, but at the expense of representing every person.

Then, I thought this would stop at using the U-space vectors (the ones that form the basis of the PCA image) and their corresponding ellipse to form our color space, but no, the function fitting is a very slick idea, even if it was executed by hand.

Lastly, I love the presentation of sampling from different r values. Whether you sample from a fixed r value or a range of r values, I bet this has great applications in game design or animation.

I still don't quite get the manual data labeling process at the beginning? It seems like it would encode some bias, but the consistency of the first point cloud and the results certainly speak for themselves.

For anyone confused, turn off your dark mode extension. :)
Love it. I especially thought the introspective “aside” section on related resources was great, and I wish more people would show this kind of reflection.
This is excellent work! You’ve got a 49 year old and a 10 year old equally into it. That’s impressive - nice work.
On the movie Dolemite by Eddy Murphy, they go over the fact that black people absorb light and white people reflect, and how that changes the motion picture shooting process totally. Also how one size does not fit all. Cool project! I am not much into the humanities part of the project. For me this is as natural as having a localization framework, just in this case for skin tones.
I love this! Such a beautiful use of some real nerdy math to benefit humans in a way non-nerds would appreciate.
Very neat project. Could I use this code to generate skin tones in my own project? Or more meant to just be educational/inspirational? I guess I'm wondering if you've considered adding a license.
Skin is so interesting as a surface to think about how light passes through and bounces off of.

There is at least one article published by a technical artist at Pixar who describes modeling a skull within a human scan so that subsurface lighting is more accurately rendered.

I suspect you could combine this with dr_scully’s comment and GolDDranks’ to reach the nuance involved in long tail realism details.

Interesting though that the 1.5 setting (at least on my older iPhone) doesn’t really ever seem to cover the range of skin tones of indigenous Australians (“aboriginal” and Torres Strait Islanders), who apparently get their skin tones from a somewhat different expression of genes than other peoples with darker skin.

The 2.0 “outliers” cover those skin tones.

Masai and some Somali skin tones, similarly, look better represented by the outliers.

The full range of possible human skin tones is perhaps a bit of a challenge for technical colour representation, partly because diffuse reflectance seems to vary so much and that is hard to approximate on screen (e.g. as any website designer could attest, the difference between representing silver and grey is the use of highlights), though the representation of skin tones is a lot better than the early colour film era.

Never seen anyone #E6FFF8 (bottom right corner).

An albino that consumed too much colloidal silver for years?

Skin tones are particularly difficult to pin down, besides the pigmentation there are two effects at play: 1) sub surface scattering (light goes thru and bounces under the skin a bit) and 2) some infra-red emission (the responsible for making some people appear magenta on digital photography)

So even when you get the palette right, to paint it like a believable material in a convincing way is still super hard!

If you're ##CCFFFF please go to the hospital
Not my domain though I followed the data science enough to nod as if I really followed it,

but this is just lovely and inspirational work. A unique marriage of hacking in the celebratory sense, thoughtfulness, and meaningful contribution. Outstanding.