Walker-Independent Features for Gait Recognition from Motion Capture Data

@article{Balazia2016WalkerIndependentFF,
  title={Walker-Independent Features for Gait Recognition from Motion Capture Data},
  author={Michal Balazia and Petr Sojka},
  journal={ArXiv},
  year={2016},
  volume={abs/1609.06936}
}
MoCap-based human identification, as a pattern recognition discipline, can be optimized using a machine learning approach. Yet in some applications such as video surveillance new identities can appear on the fly and labeled data for all encountered people may not always be available. This work introduces the concept of learning walker-independent gait features directly from raw joint coordinates by a modification of the Fisher’s Linear Discriminant Analysis with Maximum Margin Criterion. Our… 

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