Subspace Classification for Face Recognition

Raffaele Cappelli, Dario Maio, Davide Maltoni

Abstract: This paper introduces a new subspace classification approach for face recognition. One or more MKL subspaces are created for each individual, starting from the feature vectors extracted through a bank of Gabor filters. The advantages of this method with respect to other well-know approaches are experimentally proved; in particular, our subspace approach effectively captures the intra-class variability, thus allowing to better discriminate between known and unknown faces.