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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Autori principali:	Sarah Altowairqi, Suhuai Luo, Peter Greer, Shan Chen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2024-05-01
Serie:	Applied Sciences
Soggetti:	crowd anomaly detection visual descriptor sparse feature tracking neural networks
Accesso online:	https://www.mdpi.com/2076-3417/14/9/3928
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