Analysis of methods for detection of anomalies in video series of video surveillance camera on vehi-cles

Abstract

Problem. Video surveillance is a process of monitoring various objects, which is implemented with the use of video cameras - optical-electronic and microprocessor devices, designed for visual control of the environment, with the aim of the safety of life, activity and property of a modern person. Such processes and objects can be, for example, cars moving at an intersection, on a street or on a country road, a road surface during the control of its condition and quality, a security system of any infrastructure object. Goal. The purpose of the study is the analysis of the technical composition of systems for detecting anomalies in the video of video surveillance cameras and a comparative review of computational methods for processing the results of this observation. To achieve the goal, it is necessary to research literary sources, that is, articles in scientific journals, reports at conferences, articles on non-thematic web portals, monographs and textbooks, the names of which indicate the possibility of finding information useful for this research. Methodology. As part of the research task, we are interested in the technologies, systems and methods that have been proposed and developed for obtaining, processing and analyzing video sequences and images, including machine vision tasks, image classification, object and anomaly detection, image segmentation, etc. Results. As a result of this research, the following was done: 1) An overview of the main modern systems for detecting anomalies in the video series of video surveillance cameras was conducted. It was concluded that the differences between the anomaly detection systems in the video series of video surveillance cameras are due to the choice of methods for processing video information. 2) An analysis of methods of detecting anomalies in the video series of video surveillance cameras was carried out. For this purpose, a classification of modern methods of detecting anomalies in the video series was developed and the basics of the theory of deep neural networks were considered in terms of the possibility of their application for classification, localization, segmentation, detection, identification and tracking of objects in the video series of surveillance cameras. Originality. An overview of the main modern systems for detecting anomalies in the video series of video surveillance cameras was conducted. It was concluded that the differences between the systems for searching for anomalies in the video series of video surveillance cameras are determined by the choice of methods for processing video information. An analysis of the methods of detecting anomalies in the video series of video surveillance cameras was carried out. Practical value. The developed information system is already used to provide students of all educational institutions of Ukraine of the III level of accreditation with the information about our university; regarding the specialties offered by the university and the corresponding professions; regarding open days, preparatory courses and much more.