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      PIR-sensor based human motion event classification

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      Author
      Urfaliog̃lu O.
      Soyer, E.B.
      Töreyin, B.U.
      Çetin, A.E.
      Date
      2008
      Source Title
      2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      In this paper, we use a modified Passive Infrared Radiation or Pyroelectric InfraRed (PIR) sensor to classify 5 different human motion events with one additional 'no action' event. Event detection enables new applications in environments hosting dynamic processes. Typical event detection applications are based on audio or video sensor data. Given a data stream, often the task is to find or classify specific dynamic processes. Most of the applications for the monitoring of human activities in an environment are based on video sensor data. As an alternative or complementary approach, low cost PIR sensors can be used for such applications. The classification is done by a bayesian approach using Conditional Gaussian Mixture Models (CGMM) trained for each class. We show in experiments that using PIR-sensors, different human motion events in a room can be successfully detected. ©2008 IEEE.
      Keywords
      Bayesian approaches
      Data streams
      Dynamic processes
      Event classifications
      Event detections
      Gaussian Mixture models
      Human activities
      Human motions
      Low costs
      New applications
      Pir sensors
      Pyroelectric infrared sensors
      Video sensors
      Animal cell culture
      Applications
      Bayesian networks
      Infrared radiation
      Signal processing
      Sensors
      Permalink
      http://hdl.handle.net/11693/26831
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2008.4632611
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      • Department of Electrical and Electronics Engineering 3337

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