PIR-sensor based human motion event classification
Author
Urfaliog̃lu O.
Soyer, E.B.
Töreyin, B.U.
Çetin, A.E.
Date
2008Source Title
2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
Language
Turkish
Type
Conference PaperItem Usage Stats
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Show full item recordAbstract
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 approachesData 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/11693/26831Published Version (Please cite this version)
http://dx.doi.org/10.1109/SIU.2008.4632611Collections
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