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      • Department of Electrical and Electronics Engineering
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      Human activity recognition using tag-based localization

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      Author
      Yurtman, Aras
      Barshan, Barshan
      Date
      2012-04
      Source Title
      Proceedings of the 20th IEEE Conference on Signal Processing and Communications Applications, 2012
      Publisher
      IEEE
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      This paper provides a comparative study on the different techniques of classifying human activities using a tag-based radio-frequency (RF) localization system. Non-uniformly-sampled data containing position measurements of the tags on the body is first converted to a uniformly-sampled one using different curve-fitting algorithms. Then, the data is partitioned into segments. Finally, various classification techniques are applied to classify human activities. Curve-fitting, segmentation, and classification methods are compared using different cross-validation techniques and the combination resulting in the best performance is presented. The results indicate that the system demonstrates acceptable performance despite the fact that tag-based RF localization is not very accurate.
      Keywords
      Classification methods
      Classification technique
      Comparative studies
      Cross-validation technique
      Human activities
      Human activity recognition
      Localization system
      Radio frequencies
      Tag-based
      Signal processing
      Curve fitting
      Permalink
      http://hdl.handle.net/11693/28211
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2012.6204571
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