[Numpy-discussion] confusion about eigenvector

[harryos]

> -------------
> from scipy import linalg
> facearray-=facearray.mean(0) #mean centering
> u, s, vt = linalg.svd(facearray, 0)
> scores = u*s
> facespace = vt.T
> # reconstruction: facearray ~= dot(scores, facespace.T)
> explained_variance = 100*s.cumsum()/s.sum()

hi
i am a newbie in this area of eigenface based methods..is this how to
reconstruct face images from eigenfaces?
facearray ~= dot(scores, facespace.T)
i guess it translates to
facearray = dot(sortedeigenvectorsmatrix , facespace)

i tried it and it produces (from facearray) a set of images very
similar(but dark and bit smudged around eyes,nose..) to the original
set of face images..
oharry