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I'm using Fisherfaces for face classification of race and gender and I cannot get it better then about 80%. Wondering if anyone has any tips on improving it. Note I'm also trying various matlab fisherface scripts aswell and all are about 80% accurate.

Note that the things I've tried is: 1. Increasing the name of training images. But I find 80 images is about the maximum where there is only marginal improvement when it is more than that.

1. Instead of using the best picked face match, instead get the average of the top three. Eg if face one is male, face 2 is female and face 3 is female then choose female as the gender. But I find this gives worse results than just picking the best matched face.

2. Changing normalisation, contrast etc of the images. But I find this only has a marginal effect on the accuracy.

I'm using Fisherfaces for face classification of race and gender and I cannot get it better then about 80%. Wondering if anyone has any tips on improving it. Note I'm also trying various matlab fisherface scripts aswell and all are about 80% accurate.

Note that the things I've tried is: 1. is:

1. Increasing the name of training images. But I find 80 images is about the maximum where there is only marginal improvement when it is more than that.

   1. Instead of using the best picked face match, instead get the average of the top three. Eg if face one is male, face 2 is female and face 3 is female then choose female as the gender. But I find this gives worse results than just picking the best matched face.

   2. Changing normalisation, contrast etc of the images. But I find this only has a marginal effect on the accuracy.