alt Hacker NewsThis 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.
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Thank you! I call out the manual labeling bias and also that a future work improvement would be to be scientific about that labeling process (multiple labelers, expert labelers), and then to feed that into the equation generation steps. Part of where the "good enough" naming comes from - I was hoping that using my art brain and keeping a bunch of reference images in mind (shout out to the Humanae project) would maybe offset the bias a bit. But 100% right on the bias being there.
If you look at my doctoral thesis, in fact skin colour can be parametrised using melanin and haemoglobin concentration; which it means it is indeed (roughly) two dimensional. This allows you to invert the colour of a pixel and identify someone’s chromophore concentration. This is based on previous work of others cited in the thesis.
https://discovery.ucl.ac.uk/id/eprint/10093345/