Micro Expression Recognition

Micro-expression recognition (MER) focuses on automatically identifying subtle, fleeting facial expressions that reveal concealed emotions. Current research emphasizes improving the accuracy of MER systems by developing advanced deep learning models, such as transformer networks and graph convolutional networks, often incorporating techniques like motion magnification, attention mechanisms, and transfer learning from macro-expressions to address challenges posed by limited data and the subtle nature of micro-expressions. These advancements hold significant potential for applications in various fields, including lie detection, psychotherapy, and human-computer interaction, by providing objective measures of emotional states. The development of robust and efficient MER systems remains a key focus, with ongoing efforts to improve feature extraction, model design, and cross-database generalization.