Building a Moving Object Identification System Based on Machine Learning Technologies

Abstract

The study is devoted to the construction of a system for identifying moving objects in a video stream based on machine learning technologies. Tracking and recognizing moving objects is an urgent task of our time. It is important to recognize objects in motion and identify them based on artificial intelligence. The system is divided into three main modules: face recognition, people tracking, and saving of recognition results. The use of modern technologies and YOLOv7 machine learning algorithms for tracking people and the Face Recognition library for face recognition is described. A contextual Data flow diagram is created, which shows the sequence of steps required to convert the input video stream into normalized face images that are ready for further recognition. The hierarchy of processes of the moving object identification system is built. The video processing process decomposition diagram shows the logical sequence of stages and data flows required to prepare face images. Behavior classification associates detected motion patterns with specific types of behavior. The system uses facial identification data and information about their previous behavior to classify movement patterns. The process decomposition allowed us to consider in detail each of the key aspects of the system and reveal the sequence of steps and data flows required for their implementation. Building a process hierarchy diagram made it possible to qualitatively display the relationships between all processes and subprocesses of the system, demonstrating the logical sequence of their execution. The ER diagram defined the structure of the database used to store information about individuals. The system analysis laid the foundation for the further design and development of the information system for tracking and recognizing people. It allowed us to determine the main functional requirements, the structure of the system and the relationships between its components. particular importance is the ability to use the software to prevent terrorist and sabotage threats. Thanks to such information systems, it is possible to improve the economic situation of both individual facilities and the country as a whole.