Group and collaborative dictionary pair learning for face recognition

Abstract

In this paper, three new algorithms are presented by applying group idea and collaborative thought to projective dictionary pair learning (DPL). These algorithms further extend the framework of discriminative dictionary learning (DL). Based on projective dictionary pair learning which realizes the goals of signal representation and pattern classification by learning a synthesis dictionary and an analysis dictionary at the same time, this paper successfully facilitates group idea and collaborative thought into projective dictionary pair learning. The application of these methods not only leads to very competitive accuracies in face recognition tasks compared with DPL, but also greatly reduces the time complexity in training and test stages, compared with conventional DL methods.