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In this paper, we explore bilinear and elastically deformable models for addressing jointly 3D face and facial expression recognition. An elastically deformable model is built first to allow anatomically valid point-to-point correspondence among face surfaces and then, bilinear models are used to decouple the impact of identity and expression on face appearance. This enables the representation of the surface using two independent sets of control coefficients that can be used for joint face and facial expression recognition. The proposed system was tested on the publicly available BU-3DFE face database where an average facial expression recognition rate of 89.5% and a rank-1 face recognition rate of 85% were achieved.