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Detection of aberrant behaviour in home environments from video sequence

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Abstract

We introduce an application for the detection of aberrant behaviour within home based environments, with a focus on repetitive actions, which may be present in instance of persons suffering from dementia. Video based analysis has been used to detect the motion of a person within a given scene in addition to tracking them over the time. Detection of repetitive actions has been based on the analysis of a person’s trajectory using the principles of signal correlation. Along with the ability to detect repetitive motion the developed approach also has the ability to measure the amount of activity/inactivity within the scene during a given period of time. Our results showed that the developed approach had the ability to detect all patterns in the data set examined with an average accuracy of 96.67%. This work has therefore validated the proposed concept of video based analysis for the detection of repetitive activities.

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Authors and Affiliations

  1. Czech Technical University in Prague, Prague, Czech Republic

    Zdenka Uhríková & Václav Hlaváč

  2. School of Computing and Mathematics, University of Ulster, Jordanstown, Northern Ireland, UK

    Chris D. Nugent

  3. Belfast City Hospital, Queen’s University of Belfast, Belfast, Northern Ireland, UK

    David Craig

Authors
  1. Zdenka Uhríková
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  2. Chris D. Nugent
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  3. David Craig
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  4. Václav Hlaváč
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Corresponding author

Correspondence to Zdenka Uhríková.

Additional information

This work was supported by European Commission Project MEST-CT-2005-021024 and by Czech Ministry of Education project 1M0567.

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Uhríková, Z., Nugent, C.D., Craig, D. et al. Detection of aberrant behaviour in home environments from video sequence. Ann. Telecommun. 65, 571–581 (2010). https://doi.org/10.1007/s12243-010-0179-x

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  • DOI: https://doi.org/10.1007/s12243-010-0179-x

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