Abstract
Facial expression recognition is an academic subject, and it can be applied not only in the field of computer vision but also in psychology and sociology. This paper proposed a robust dynamic facial expression recognition method which using hybrid features and the PSOELM (Particle Swarm Optimization-Extreme Learning Machine) model. At first, six PSOELM models were trained on the training set of six basic expressions, respectively. Then by extracting the hybrid features which fusing geometric features and texture features, the dynamic expressions were recognized by PSO-ELM models. These experiments were performed on the Cohn-Kanade+ face database. The results show that this method has a better recognition effect on dynamic facial expression recognition.
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