Deep Learning Based on Facial Expression Recognition from Images to Videos

Facial expressions, as a vital conduit for human emotional expression, are among the most observable features of machines in the field of computer vision. Consequently, facial expression recognition holds broad potential for applications in artificial intelligence and health monitoring, among others. Given the diversity and complexity of expressions, the development of efficient and accurate models for expression recognition is of significant importance. This paper systematically reviews the foundational knowledge and related research in facial expression recognition, analyzing the application of current primary models in expression recognition. Employing a combination of literature review and experimental analysis, this study evaluates existing facial expression recognition algorithms. Special attention is given to advanced models based on Convolutional Neural Networks (CNNs), with a detailed comparison of their architectures and characteristics, analyzing their performance under various conditions. The paper concludes with a summary of the latest advancements in the field of facial expression recognition and proposes potential directions for future research.