Viewpoint independent face recognition by competition of the viewpoint dependent classifiers

摘要

This paper proposes a viewpoint invariant face recognition method in which several viewpoint dependent classifiers are combined by a gating network. The gating network is designed as autoencoder with competitive hidden units. The viewpoint dependent representations of faces can be obtained by this autoencoder from many faces with different views. By using this autoencoder as the gating network in the mixture of experts (classifiers) architecture, the network can be self-organized such that one of the classifiers is selectively activated depending on the viewpoint of a given face image. Experimental results of view invariant face recognition are shown using the face images captured from different viewpoints.