Abstract
This chapter introduces a novel framework for detecting anomalies as change points. This chapter presents a general approach for change point detection, which can be used for behaviour analysis (where periods between change points are considered as different behaviours) and anomaly detection (where a change is considered as a break point between normal and abnormal behaviours). In the proposed framework changes are considered as functional breaks in input data.
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Notes
- 1.
The implementation in Matlab 2016a is used (the function findchangepts).
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Isupova, O. (2018). Change Point Detection with Gaussian Processes. In: Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-75508-3_5
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DOI: https://doi.org/10.1007/978-3-319-75508-3_5
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