TR2021-029
A Survey of Single-Scene Video Anomaly Detection
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- "A Survey of Single-Scene Video Anomaly Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2020.3040591, Vol. 44, No. 5, pp. 2293-2312, November 2020.BibTeX TR2021-029 PDF
- @article{Jones2020nov,
- author = {Jones, Michael J. and Ramachandra, Bharathkumar and Vatsavai, Ranga},
- title = {A Survey of Single-Scene Video Anomaly Detection},
- journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
- year = 2020,
- volume = 44,
- number = 5,
- pages = {2293--2312},
- month = nov,
- doi = {10.1109/TPAMI.2020.3040591},
- url = {https://www.merl.com/publications/TR2021-029}
- }
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- "A Survey of Single-Scene Video Anomaly Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2020.3040591, Vol. 44, No. 5, pp. 2293-2312, November 2020.
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Abstract:
This survey article summarizes research trends on the topic of anomaly detection in video feeds of a single scene. We discuss the various problem formulations, publicly available datasets and evaluation criteria. We categorize and situate past research into an intuitive taxonomy and provide a comprehensive comparison of the accuracy of many algorithms on standard test sets. Finally, we also provide best practices and suggest some possible directions for future research.