Corpus ID: 86375060

Heterogeneous face recognition

@inproceedings{Jain2012HeterogeneousFR,
  title={Heterogeneous face recognition},
  author={Anil K. Jain and Brendan Klare},
  year={2012}
}
One of the most difficult challenges in automated face recognition is computing facial similarities between face images acquired in alternate modalities. Called heterogeneous face recognition (HFR), successful solutions to this recognition paradigm would allow the vast collection of face photographs (acquired from driver's licenses, passports, mug shots, and other sources of frontal face images) to be matched against face images from alternate modalities (e.g. forensic sketches, infrared images… 
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References

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    IEEE Transactions on Pattern Analysis and Machine Intelligence
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TLDR
A generic HFR framework is proposed in which both probe and gallery images are represented in terms of nonlinear similarities to a collection of prototype face images, and Random sampling is introduced into the H FR framework to better handle challenges arising from the small sample size problem.
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TLDR
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TLDR
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TLDR
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TLDR
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