Variational Feature Representation-based Classification for face recognition with single sample per person

@article{Ding2015VariationalFR,
  title={Variational Feature Representation-based Classification for face recognition with single sample per person},
  author={Ru-Xi Ding and Daniel K. Du and Zheng-Hai Huang and Zhi-Ming Li and Kun Shang},
  journal={J. Visual Communication and Image Representation},
  year={2015},
  volume={30},
  pages={35-45}
}
The single sample per person (SSPP) problem is of great importance for real-world face recognition systems. In SSPP scenario, there is always a large gap between a normal sample enrolled in the gallery set and the non-ideal probe sample. It is a crucial step for face recognition with SSPP to bridge the gap between the ideal and non-ideal samples. For this purpose, we propose a Variational Feature Representation-based Classification (VFRC) method, which employs the linear regression model to fit… CONTINUE READING

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