• Computer Science
  • Published in MVA 2005

Unsupervised Abnormality Detection in Video Surveillance

@inproceedings{Nanri2005UnsupervisedAD,
  title={Unsupervised Abnormality Detection in Video Surveillance},
  author={Takuya Nanri and Nobuyuki Otsu},
  booktitle={MVA},
  year={2005}
}
The detection of abnormal movements is an important problem in video surveillance applications. We propose an unsupervised method for abnormal movement detection in scenes containing multiple persons. Our method uses cubic higher-order local auto-correlation (CHLAC) to extract movement features. We show that the additive property of CHLAC in combination with a linear subspace method is well suited to simplify the learning of normal movements and to detect abnormal movements even in scenes… CONTINUE READING

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