Efficient Crowd Anomaly Detection Using Sparse Feature Tracking and Neural Network

Crowd anomaly detection is crucial in enhancing surveillance and crowd management. This paper proposes an efficient approach that combines spatial and temporal visual descriptors, sparse feature tracking, and neural networks for efficient crowd anomaly detection. The proposed approach utilises diver...

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Главные авторы:	Sarah Altowairqi, Suhuai Luo, Peter Greer, Shan Chen
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2024-05-01
Серии:	Applied Sciences
Предметы:	crowd anomaly detection visual descriptor sparse feature tracking neural networks
Online-ссылка:	https://www.mdpi.com/2076-3417/14/9/3928
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