Compressive Sensing of Time Series for Human Action Recognition

@article{Prez2010CompressiveSO,
  title={Compressive Sensing of Time Series for Human Action Recognition},
  author={{\'O}scar P{\'e}rez and Richard Y. D. Xu and Massimo Piccardi},
  journal={2010 International Conference on Digital Image Computing: Techniques and Applications},
  year={2010},
  pages={454-461}
}
Compressive Sensing (CS) is an emerging signal processing technique where a sparse signal is reconstructed from a small set of random projections. In the recent literature, CS techniques have demonstrated promising results for signal compression and reconstruction. However, their potential as dimensionality reduction techniques for time series has not been significantly explored to date. To this aim, this work investigates the suitability of compressive-sensed time series in an application of… CONTINUE READING