Publication details for Professor Toby BreckonAdey, P., Bordewich, M., Breckon, T.P. & O.K. Hamilton (2019), Region Based Anomaly Detection With Real-Time Training and Analysis, 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). Boca Raton, Florida, USA, IEEE, Piscataway, NJ, 495-499.
- Publication type: Conference Paper
- DOI: 10.1109/ICMLA.2019.00092
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
We present a method of anomaly detection that is capable of real-time operation on a live stream of images. The real-time performance applies to the training of the algorithm as well as subsequent analysis, and is achieved by substituting the region proposal mechanism used in  with one that makes the overall method more efficient. where they generate thousands of regions per image, we generate far fewer but better targeted regions. We also propose a 'convolutional' variant which does away with region extraction altogether, and propose improvements to the density estimation phase used in both variants.