How to improve accuracy rate on Eigenface Algorithm

Question

I use EmguCV library(openCV wrapper) on C# to implemented face detection and facial recognition using Eigenface algorithm

I found many mistakes of accuracy rate such as minimum distance is not a same person in Training Set, person who doesn't exist in Training Set but match with person in Training set with good distance, etc.

please help me.

Thank you.

additional information: - I use 1 facial image per 1 person in Training set (straight facial image, no orientation) - Now, I test with around 10-20 people in Training set

Answer 1

Try blurring the images. Since you are only using one training image per person, Eigenface does not have a way to tell whether the high-frequency component or low-frequency component would be more useful.

To decide on how much to blur / downscale the images, do an experiment with a human. Give a person some blurred test image pairs and ask them to match. Try to find out how much you can blur the images and still be successful at matching them. Use the same blurring parameters for the computer.

Image alignment techniques may also help. For example, normalize the images so that the tip of nose, and the two eyes (forming a triangle) are affine-transformed to a standard set of locations.

Finally, some simple eigenvalue preprocessing techniques or image preprocessing techniques (such as histogram equalization) may help.