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Finding behavioural anomalies in public areas using video surveillance data
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
Saab Microwave Systems, Saab AB, Gothenburg, Sweden.
2008 (English)In: Proceedings of the 11th International Conference on Information Fusion, IEEE conference proceedings, 2008, p. 1655-1662Conference paper, Published paper (Refereed)
Abstract [en]

 In this paper we propose an approach forvdetecting anomalies in data from visual surveillancevsensors. The approach includes creating a structure for representing data, building “normal models” by filling the structure with data for the situation at hand, and finally detecting deviations in the data. The approach allows detections based on the incorporation of a priori knowledge about the situation and on data-driven analysis. The main advantages with the approach compared to earlier work is the low computational requirements, iterative update of normal models and a high explainability of found anomalies. The proposed approach is evaluated off-line using real-world data and the results support that the approach could be used to detect anomalies in real-time applications.

 

Place, publisher, year, edition, pages
IEEE conference proceedings, 2008. p. 1655-1662
Keywords [en]
Anomaly detection, visual surveillance, behaviour modelling
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3607DOI: 10.1109/ICIF.2008.4632410Scopus ID: 2-s2.0-56749117785ISBN: 978-3-00-024883-2 OAI: oai:DiVA.org:his-3607DiVA, id: diva2:291095
Available from: 2010-01-29 Created: 2010-01-29 Last updated: 2017-11-27

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Brax, ChristofferNiklasson, Lars

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CiteExportLink to record
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Citation style
  • apa
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  • vancouver
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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