• DocumentCode
    3669658
  • Title

    Detecting unusual inactivity by introducing activity histogram comparisons

  • Author

    Rainer Planinc;Martin Kampel

  • Author_Institution
    Computer Vision Lab, Vienna University of Technology, Favoritenstrasse 9-11/183-2, A-1040, Austria
  • Volume
    2
  • fYear
    2014
  • Firstpage
    313
  • Lastpage
    320
  • Abstract
    Unusual inactivity at elderly´s homes is an evidence that help is needed. Hence, the automatic detection of abnormal behaviour with a low number of false positives is desired. The aim of this work is to improve the accuracy of inactivity detection by introducing a new approach based on histogram comparison in order to reliably detect abnormal behaviour in elderly´s homes. The proposed approach compares activity histograms with a pre-trained reference histogram and detects deviations from normal behavior. Evaluation is performed on a dataset containing 103 days of activity, where six days were reported as containing “unusual” inactivity (i.e., longer absence from home) by an elderly couple.
  • Keywords
    "Histograms","Sensors","Tracking","Training","Training data"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
  • Type

    conf

  • Filename
    7294947