Gaussian Process Regression-Based Video Anomaly Detection and Localization With Hierarchical Feature Representation
This paper presents a hierarchical framework for detecting local and global anomalies via hierarchical feature representation and Gaussian process regression (GPR) which is fully non-parametric and robust to the noisy training data, and supports sparse features. While most research on anomaly detect...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 24(2015), 12 vom: 25. Dez., Seite 5288-301 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2015
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Online verfügbar |
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