Improved combination of LBP and sparse representation based classification (SRC) for face recognition
Recently, local binary patterns (LBP) based descriptors and sparse representation based classification (SRC) become both eminent techniques in face recognition. Preliminary techniques of combining LBP and SRC have been proposed in the literature. However, the state-of-art method suffers from the “curse of dimensionality” for real world scenarios. In this paper, a novel face recognition algorithm of combining LBP with SRC is proposed; in which the dimensionality problem is resolved by divide-and-conquer and the discriminative power is strengthen via its pyramid architecture. The proposed face recognition method is evaluated on AR Face Database and yields very impressive results.