Fuzzy Sets for Human Fall Pattern Recognition

  • Marina V. Sokolova
  • Antonio Fernández-Caballero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7329)

Abstract

Vision-based fall detection is a challenging problem in pattern recognition. This paper introduces an approach to detect a fall as well as its type in infrared video sequences. The regions of interest of the segmented humans are examined image by image though calculating geometrical and kinematic features. The human fall pattern recognition system identifies true and false falls. The fall indicators used as well as their fuzzy model are explained in detail. The fuzzy model has been tested for a wide number of static and dynamic falls.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marina V. Sokolova
    • 1
    • 2
  • Antonio Fernández-Caballero
    • 1
    • 3
  1. 1.Instituto de Investigación en Informática de Albacete (I3A)Universidad de Castilla-La ManchaAlbaceteSpain
  2. 2.South-West State UniversityKurskRussia
  3. 3.Departamento de Sistemas InformáticosUniversidad de Castilla-La ManchaAlbaceteSpain

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