A Face Recognition Scheme Based on Embedded Hidden Markov Model and Selective Ensemble Strategy

As an effective method, the embedded hidden Markov model (E-HMM) has been widely used in pattern recognition. On applying the E-HMM to face recognition, the performance heavily depends on the selection of model parameters. Aiming at the problem of model selection, a selective ensemble of multi E-HMMs based face recognition algorithm is proposed. Experimental results illustrate that compared with the traditional E-HMM based face recognition algorithm the proposed method cannot only obtain better and more stable recognition performance, but also achieve higher generalization ability.