[Numpy-discussion] eigenvector and eigenface

[royG]

friends
I am learning eigenfaces using numpy . i use data from N images and
create eigenvectors to  get a 'sorted eigenvectors' array of size N X
N. when i project the 'zero mean imagedata' i will get a facespace
array of N X numpixels. (where numpixels is total pixels in one image)

is eigenface the same as eigenvector? some of the docs i
read(pissarenko-Eigenface-based facial recognition), use these two
words to mean the same thing..but when i look at the dimensions of
'sorted eigenvectors' array
it is only NXN and i don't know how i can make  images out of it
representing eigenfaces.

on the other hand the projection of 'zero mean imagedata' on
eigenvectors by using numpy.dot(eigenvectors,zeromeanimagedata) can
make an array of N X numpixels
 .I believe this is what is known as the facespace .is this what
represents the eigenface images ?

will be thankful for any expert opinion on this..
RG