A Double-Deep Spatio-Angular Learning Framework for Light Field-Based Face Recognition

@article{SepasMoghaddam2020ADS,
  title={A Double-Deep Spatio-Angular Learning Framework for Light Field-Based Face Recognition},
  author={Alireza Sepas-Moghaddam and Mohammad A. Haque and Paulo Lobato Correia and Kamal Nasrollahi and Thomas Baltzer Moeslund and Fernando Pereira},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2020},
  volume={30},
  pages={4496-4512}
}
Face recognition has attracted increasing attention due to its wide range of applications, but it is still challenging when facing large variations in the biometric data characteristics. Lenslet light field cameras have recently come into prominence to capture rich spatio-angular information, thus offering new possibilities for advanced biometric recognition systems. This paper proposes a double-deep spatio-angular learning framework for light field-based face recognition, which is able to… Expand
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