On Reducing the Effect of Covariate Factors in Gait Recognition: A Classifier Ensemble Method

@article{Guan2015OnRT,
  title={On Reducing the Effect of Covariate Factors in Gait Recognition: A Classifier Ensemble Method},
  author={Yu Guan and Chang-Tsun Li and Fabio Roli},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={1521-1528}
}
Robust human gait recognition is challenging because of the presence of covariate factors such as carrying condition, clothing, walking surface, etc. In this paper, we model the effect of covariates as an unknown partial feature corruption problem. Since the locations of corruptions may differ for different query gaits, relevant features may become irrelevant when walking condition changes. In this case, it is difficult to train one fixed classifier that is robust to a large number of different… CONTINUE READING
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