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Sequential Conformal Anomaly Detection in Trajectories based on Hausdorff Distance
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-8884-2154
2011 (Swedish)In: Proceedings of the 14th International Conference on Information Fusion (FUSION 2011), IEEE Computer Society, 2011, 153-160 p.Conference paper, Published paper (Refereed)
Abstract [en]

Abnormal behaviour may indicate important objects and situations in e.g. surveillance applications. This paper is concerned with algorithms for automated anomaly detection in trajectory data. Based on the theory of Conformal prediction, we propose the Similarity based Nearest Neighbour Conformal Anomaly Detector (SNN-CAD) which is a parameter-light algorithm for on-line learning and anomaly detection with wellcalibrated false alarm rate. The only design parameter in SNN-CAD is the dissimilarity measure. We propose two parameterfree dissimilarity measures based on Hausdorff distance for comparing multi-dimensional trajectories of arbitrary length. One of these measures is appropriate for sequential anomaly detection in incomplete trajectories. The proposed algorithms are evaluated using two public data sets. Results show that high sensitivity to labelled anomalies and low false alarm rate can be achieved without any parameter tuning.

Place, publisher, year, edition, pages
IEEE Computer Society, 2011. 153-160 p.
Keyword [en]
Anomaly detection, trajectory data, Conformal prediction, Hausdorff distance, automated surveillance
National Category
Computer Science
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-5687Scopus ID: 2-s2.0-80052522144ISBN: 978-1-4577-02067-9 (print)OAI: oai:DiVA.org:his-5687DiVA: diva2:514042
Conference
14th International Conference on Information Fusion, Fusion 2011;Chicago, IL;5 July 2011–8 July 2011
Available from: 2012-04-04 Created: 2012-04-04 Last updated: 2014-05-05Bibliographically approved

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Scopushttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5977571

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf