Micro-expression recognition system

Micro-expressions are rapid involuntary facial expressions which reveal one's genuine emotions people trying to disguise. To the best of our knowledge, few works have been done in designing a micro-expression recognition visual platform. In this paper, we preliminarily study micro-expression recognition and subsequently develop a micro-expression visual platform that includes feature expression, dimension reduction as well as real-time video testing, etc. The platform leverages Gabor wavelet filter for expression feature extraction, principal components analysis (PCA) and linear discriminant analysis (LDA) for dimension reduction, and support vector machine (SVM) for expression classification. By using the trained model of the platform, we are able to test against micro-expression recognition. Experimental results show that the proposed scheme performs well on the CASME II database. Besides, it also works well on real-time expression recognition.