Face Micro-expression Recognition Based on Online Sequence Limit Learning Machine

Face micro-expression recognition is a popular research area combining machine vision and image recognition, and is an important branch of face recognition technology, the core of which is feature extraction and classification recognition. In this paper, the feature extraction and dimensionality reduction of micro-expressions are performed by combining Gabor wavelet transform and principal component analysis methods, and then an online sequence limit learning machine classifier is first trained and then tested to complete the classification and recognition of micro-expressions. This paper further validates the feasibility of the method by using the publicly available JAFFE expression dataset for micro-expression recognition experiments in Matlab to obtain the recognition accuracy.