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Development of an algorithm for abnormal human behavior detection in intelligent video surveillance system
Автор(ы)
Дата публикации
1 марта 2021 г.
Тип
conference paper
Издатель
IOP Publishing
Журнал
IOP Conference Series Materials Science and Engineering
Том
1069
Выпуск
1
Первая страница
012046
Последняя страница
012046
ISSN
1757-8981
Аннотация
Abstract The aim of the work is to develop algorithms for analyzing video data in real time based on computer vision methods, as well as deep learning technologies for artificial neural networks for abnormal human behavior recognition near critical facilities using ATMs as an example. The article provides an overview of the initial research aimed at the choice of data capture devices, neural network architecture, software implementation and selection of experimental conditions (distance and illumination). Static and dynamic hand gestures were used as object’s movements. Experimental results show that using the Intel RealSense D435 Depth Camera provides more accurate dynamic gesture recognition under different experimental conditions.
Области науки (FoS)