Non-frontal view facial expression recognition is important in many scenarios where the frontal view face images may not be available. However, few work on this issue has been done in the past several years because of its technical challenges and the lack of appropriate databases. Recently, a 3D facial expression database (BU-3DFE database) is collected by Yin et al.  and has attracted some researchers to study this issue. Based on the BU-3DFE database, in this paper we propose a novel approach to expression recognition from non-frontal view facial images. The novelty of the proposed method lies in recognizing the multi-view expressions under the unified Bayes theoretical framework, where the recognition problem can be formulated as an optimization problem of minimizing an upper bound of Bayes error. We also propose a close-form solution method based on the power iteration approach and rank-one update (ROU) technique to find the optimal solutions of the proposed method. Extensive experiments on BU-3DFE database with 100 subjects and 5 yaw rotation view angles demonstrate the effectiveness of our method.