Facial expression recognition has been an active area of research over the past few decades, and it is still challenging due to high intra-class variation. Traditional approaches for this problem rely on hand-crafted features such as SIFT, HOG, LBP, followed by a classifier trained database images or videos. Most these works perform reasonably well datasets captured in controlled condition but ...

Abstract Micro-expression recognition is a substantive cross-study of psychology and computer science, it has wide range applications (e.g., psychological clinical diagnosis, emotional analysis, criminal investigation, etc.). However, the subtle diverse changes in facial muscles make difficult for existing methods to extract effective features, which limits improvement micro-expression accuracy...