Algorithm for identifying abnormal actions

The study is devoted to the problem of recognition of human activity recognition and the definition of normal and abnormal behavior (activity) depending on the action scene. Automated detection of abnormal activity using computer vision technologies and rapid response makes it possible to improve the work of rapid response services, thereby saving human lives or stopping offenses. The paper presents a comprehensive review of methods for recognizing human activity and detecting abnormal human activity based on deep learning. Various classifications of abnormal activity are investigated, and then deep learning methods and neural network architectures used to detect abnormal activity are discussed and analyzed. Based on the comparative analysis of various approaches, an algorithm for recognizing human activity has been proposed and a neural network has been developed that determines violent and nonviolent actions with an accuracy of 92,22% in 150 epochs.