Sparse representation of (Multiscale) histograms for face recognition robust to registration and illumination problems

We combine sparse representation with a multiresolution histogram face descriptor to create a powerful representation method for face recognition. The multi resolution histogram descriptor is based on local binary patterns or local phase coding to achieve invariance to various types of image degradation phenomena. By its nature, the histogram descriptor is also robust to geometric misalignment of the gallery and query faces. The proposed face recognition method is evaluated on Yale Face Database B and the extended Yale Face Database B, yielding very impressive results.