ML Anthology

Delta-Dual Hierarchical Dirichlet Processes: A Pragmatic Abnormal Behaviour Detector

Tom S. F. Haines, Tao Xiang
ICCV 2011 pp. 2198-2205
doi:10.1109/ICCV.2011.6126497 /iccv/2011/haines2011iccv-delta/

Abstract

In the security domain a key problem is identifying rare behaviours of interest. Training examples for these behaviours may or may not exist, and if they do exist there will be few examples, quite probably one. We present a novel weakly supervised algorithm that can detect behaviours that either have never before been seen or for which there are few examples. Global context is modelled, allowing the detection of abnormal behaviours that in isolation appear normal. Pragmatic aspects are considered, such that no parameter tuning is required and real time performance is achieved.

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Cite

Text

Haines and Xiang. "Delta-Dual Hierarchical Dirichlet Processes: A Pragmatic Abnormal Behaviour Detector." IEEE/CVF International Conference on Computer Vision, 2011. doi:10.1109/ICCV.2011.6126497

Markdown

[Haines and Xiang. "Delta-Dual Hierarchical Dirichlet Processes: A Pragmatic Abnormal Behaviour Detector." IEEE/CVF International Conference on Computer Vision, 2011.](https://mlanthology.org/iccv/2011/haines2011iccv-delta/) doi:10.1109/ICCV.2011.6126497

BibTeX

@inproceedings{haines2011iccv-delta,
  title     = {{Delta-Dual Hierarchical Dirichlet Processes: A Pragmatic Abnormal Behaviour Detector}},
  author    = {Haines, Tom S. F. and Xiang, Tao},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2011},
  pages     = {2198-2205},
  doi       = {10.1109/ICCV.2011.6126497},
  url       = {https://mlanthology.org/iccv/2011/haines2011iccv-delta/}
}