Abstract
Recognizing human emotions is one of the most urgent tasks in the field of artificial intelligence and computer vision. Modern technologies make it possible to analyze human facial expressions and emotional states in real time using various methods and tools, such as video surveillance, webcams, and specialized machine learning algorithms. This field has wide applications in various fields including medical technologies, security systems, and in the development of personalized user interfaces. The aim of this paper is to systematize existing approaches and technologies used for emotion recognition using webcams. Different methods of video data processing, including the use of facial micro-expressions, as well as features of machine learning models used for emotion classification are presented. Current algorithms and systems aimed at improving the accuracy of real-time emotion recognition will also be analyzed. The review of these methods and technologies not only allows us to assess the current level of development of the field, but also to identify promising areas for further research and improvement of existing systems.