洪銘曎 12/31

The canonical face recognition algorithm Eigenface and Fisherface are both based on one dimensional vector representation.

With the high feature dimensions, face recognition often suffers from the curse of dimension problem.

I ) what is the meaning of the eigenvalue and eigenvector of the covariancematrix in 2DPCA 2) why 2DPCA can outperform Eigenface 3) how to reduce the dimension after 2DPCA directly.