Dear all,
I am working on face recognition using Principle Component Analysis (PCA) using LabVIEW. I have been successful uptil sorting eigenvectors by their corresponding eigen-values but now can't get any clear ideas on how to project my training images in database into a new space to reduce the dimension. I had done the same using Matlab. The script for this operation in Matlab goes like this:
projectedimages = [];
number_of_images = size(eigenfaces,2);
for i = 1 : number_of_images
vector = eigenfaces'*A(:,i);
projectedimages = [projectedimages vector];
end
This part of Matlab code actually projects the training images into a new space by calculating the DOT product between image and each of the eigen-vectors. So far what I have been successful in is how to calculate eigen-vectors, sorted. Any idea how should I project my images into new space by applying precisely the aforementioned Matlab technique?
Regards.