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Many state of the art face recognition algorithms use local feature descriptors known as Local Binary Pattern (LBP). Many extensions of LBP exist, but the performance is still limited. Recently Learning Based Descriptor was introduced for face verification, it showed high discrimination power, but compared with LBP, it’s expensive to compute. In this paper, we propose a novel coding approach for Learning Based Descriptor (LE) descriptor which can keep the most discriminative LBP like feature as well as significantly shorten the feature extraction time. Since the proposed method speed up the LE descriptor’s feature extraction time, we call it Speeded Up Learning Descriptor or SULE for short. Tests on LFW standard benchmark show the superiority of SULE with respect of several state of the art feature descriptors regularly used in face verification

Speed Up Learning based Descriptor for Face Verification