| We consider the problem of computing low rank approximations of matrices. The
novelty of our approach is that the low rank approximations are on a sequenceof
matrices. Unlike the problem of low rank approximations of a single matrix,which
was well studied in the past, the proposed algorithm in this paper does notadmit
a closed form solution in general. We did extensive experiments on face imagedata
to evaluate the effectiveness of the proposed algorithm and compare thecomputed
low rank approximations with those obtained from traditional Singular Value
Decomposition based method. |