Description: In this paper, we extend Fisherface for face recognition
from one example image per son. Fisherface is one of
the most successful face recognition methods. However,
Fisherface requires several training images for each face,
so it cannot be applied to the face recognition applications
where only one example image per person is available for
training. To tackle this problem, we extended the
Fisherface method by proposing a method to derive
multiple images of a face from one single image.
Fisherface is then trained on these derived images.
Experimental results on Bern face database and our 350
subjects database show that our method makes impressive
performance improvement compared with the
conventional Eigenfaces and template matching techniques
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