Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition

@article{Taigman2011LeveragingBO,
  title={Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition},
  author={Yaniv Taigman and Lior Wolf},
  journal={CoRR},
  year={2011},
  volume={abs/1108.1122}
}
We employ the face recognition technology developed in house at face.com to a well accepted benchmark and show that without any tuning we are able to considerably surpass state of the art results. Much of the improvement is concentrated in the high-valued performance point of zero false positive matches, where the obtained recall rate almost doubles the best reported result to date. We discuss the various components and innovations of our system that enable this significant performance gap… CONTINUE READING
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The fastest face recognition algorithms on the web get even faster as face.com leverages new 2nd generation intel core processor family

  • David Speiser
  • 2011
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