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A Review of Anomaly Detection in Automated Surveillance

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3 Author(s)
Sodemann, A.A. ; Coll. of Technol. & Innovation, Arizona State Univ., Phoenix, AZ, USA ; Ross, M.P. ; Borghetti, B.J.

As surveillance becomes ubiquitous, the amount of data to be processed grows along with the demand for manpower to interpret the data. A key goal of surveillance is to detect behaviors that can be considered anomalous. As a result, an extensive body of research in automated surveillance has been developed, often with the goal of automatic detection of anomalies. Research into anomaly detection in automated surveillance covers a wide range of domains, employing a vast array of techniques. This review presents an overview of recent research approaches on the topic of anomaly detection in automated surveillance. The reviewed studies are analyzed across five aspects: surveillance target, anomaly definitions and assumptions, types of sensors used and the feature extraction processes, learning methods, and modeling algorithms.

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Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:42 ,  Issue: 6 )