Movement Primitive Segmentation for Human Motion Modeling: A Framework for Analysis

@article{Lin2016MovementPS,
  title={Movement Primitive Segmentation for Human Motion Modeling: A Framework for Analysis},
  author={Jonathan Feng-Shun Lin and Michelle Karg and Dana Kulic},
  journal={IEEE Transactions on Human-Machine Systems},
  year={2016},
  volume={46},
  pages={325-339}
}
Movement primitive segmentation enables long sequences of human movement observation data to be segmented into smaller components, termed movement primitives, to facilitate movement identification, modeling, and learning. It has been applied to exercise monitoring, gesture recognition, human-machine interaction, and robot imitation learning. This paper proposes a segmentation framework to categorize and compare different segmentation algorithms considering segment definitions, data sources… CONTINUE READING

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