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...
| Published in: | Applied Sciences |
|---|---|
| Main Authors: | Sarah Altowairqi, Suhuai Luo, Peter Greer, Shan Chen |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-05-01
|
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/9/3928 |
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