Semi-supervised Learning for Anomalous Trajectory Detection

@inproceedings{Sillito2008SemisupervisedLF,
  title={Semi-supervised Learning for Anomalous Trajectory Detection},
  author={Rowland R. Sillito and Robert B. Fisher},
  booktitle={BMVC},
  year={2008}
}
A novel learning framework is proposed for anomalous behaviour detection in a video surveillance scenario, so that a classifier which distinguishes between normal and anomalous behaviour patterns can be incrementally trained with the assistance of a human operator. We consider the behaviour of pedestrians in terms of motion trajectories, and parametrise these trajectories using the control points of approximating cubic spline curves. This paper demonstrates an incremental semi-supervised one… CONTINUE READING
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Novelty detection using extreme value statistics

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