title: ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¸ÑÑÐµÐ¼Ñ Ð²Ð¸Ð´ÐµÐ¾-Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð½ÐµÑÑÐ°ÑÐ½ÑÑ ÑÐ¸ÑÑÐ°ÑÐ¸Ð¹ Ð² Ð¾Ð±ÑÐµÑÑÐ²ÐµÐ½Ð½ÑÑ Ð·Ð°Ð²ÐµÐ´ÐµÐ½Ð¸ÑÑ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: development of a system for video detection of emergency situations in public institutions using machine learning methods
Creators: name: ÐÐ¼ÑÐ°Ð½, ÐÐ°Ð·ÐµÐ½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: Ð²Ð¸Ð´ÐµÐ¾Ð½Ð°Ð±Ð»ÑÐ´ÐµÐ½Ð¸Ñ
Ð°Ð½Ð¾Ð¼Ð°Ð»ÑÐ½ÑÐµ
Ð¾Ð¿ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¿Ð¾ÑÐ¾Ðº
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
smot
opencv
python
CCTV
abnormal
optical stream
machine learning

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description: The aim of this work is to develop a video system for detecting abnormal situations in public institutions using machine learning methods.
With the increasing number of surveillance cameras both indoors and outdoors, the relevance of developing an intelligent system that detects abnormal events through video is increasing. In general terms, advanced video surveillance can be described as an intelligent video processing technology designed to assist security personnel by providing reliable real-time alerts and supporting effective video analysis.
The work uses machine learning methods. Machine learning is a branch of artificial intelligence with its own algorithms that are capable of processing large amounts of data in real time.
In the work, intelligent video surveillance systems were studied with emphasis on finding anomalies in video surveillance, and the optical flow method was used to extract features from video frames, and then these features were processed using machine learning methods (instruction with a teacher, partial instruction and instruction without a teacher). At the end, a comparison and analysis of the results was performed and the most suitable methods were selected.
The results can be used in security systems and video surveillance to increase their efficiency.