Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories

@article{Urain2019GeneralizedMC,
  title={Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories},
  author={Julen Urain and Jan Peters},
  journal={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2019},
  pages={1363-1369}
}
  • Julen Urain, Jan Peters
  • Published 2019
  • Computer Science, Mathematics
  • 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Similarity distance measure between two trajectories is an essential tool to understand patterns in motion, for example, in Human-Robot Interaction or Imitation Learning. [...] Key Method Based on Pearson’s Correlation Coefficient and the Coefficient of Determination, our similarity metric, the Generalized Multiple Correlation Coefficient (GMCC) is presented like the natural extension of the Multiple Correlation Coefficient. The motivation of this paper is two-fold: First, to introduce a new correlation metric…Expand
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