An approach for facial expression recognition based on neural network ensemble

This paper proposes a novel method for facial expression recognition based on neural network ensemble. The facial expression features are extracted firstly through multi-expression eigenspace analysis, and then several neural networks are trained each with an eigenspace of different expressions respectively. At last their training results are aggregated as inputs of the ensemble classifier, which will provide not only the final recognition results but also the estimated expression information. Simulation results on JAFEE dataset show that the recognition accuracy of the proposed approach is better than that of the best individual neural network.