Normally you have a matrix n x p and apply PCA to it. But in the article I'm reading, the author considers that the matrix has points in it. So instead of being n x p, it'd be, say, n x p x 2. He then goes on about finding eigenvectors associated with the points and whatnot.

So, is it possible to use PCA here? All the material I've seen considers it being used with a bidimensional array. I thought about flattening the points so that instead of a three-dimensional array I'd have one with the points' coordinates interleaved, but since the eigenvalues the author talks are associated with the points and not each coordinate, I don't think that'll work.

Another thing is, supposing you're using a color image, you'd have 3 coordinates for each color which results in another three-dimensional array. The tutorials I've seen with PCA for images have use black and white images, avoiding this problem.