Skeleton Clustering by Autonomous Mobile Robots for Subtle Fall Risk Discovery

  • Yutaka Deguchi
  • Einoshin Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8502)


In this paper, we propose two new instability features, a data pre-processing method, and a new evaluation method for skeleton clustering by autonomous mobile robots for subtle fall risk discovery. We had proposed an autonomous mobile robot which clusters skeletons of a monitored person for distinct fall risk discovery and achieved promising results. A more natural setting posed us problems such as ambiguities in class labels and low discrimination power of our original instability features between safe/unsafe skeletons. We validate our three new proposals through evaluation by experiments.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yutaka Deguchi
    • 1
  • Einoshin Suzuki
    • 1
  1. 1.Department of Informatics, ISEEKyushu UniversityJapan

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