HMM+KNN classifier for facial expression recognition

Facial expression is an important communication method. Facial expression recognition has been studied in many application domains. In this paper, we study HMM and KNN classifiers, and put forward a combined approach for facial expression recognition. The basic idea of this approach is to employ the classifiers of HMM and KNN in series way. First, DHMM classifier is used to calculate the probabilities of six expressions. Then, basing on the most possible two results of classification by DHMM, the KNN classifier is used to make final decision while the difference between the maximum probability and the second is greater than the average difference. The experiment show that the performance of this method exceeds that of HMM-based only method.