Compute FAR, FRR, ERR for LBPH algorithm

Python
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Hi everyone!
I created a biometric model for facerecognition using OpenCV’s LBPH algorithm (OpenCV: Face Recognition with OpenCV).
Anyone know if it is possible to calculate evaluation metrics like FAR, FRR and ERR?

2

hmm, may i ask, what you are trying to achieve here ?
what is the exact purpose of your face recognition ?

opencv’s FaceRecognizer classes are doing “identification”
(that is, they return the closest item from a large database),
while terms like FAR and FRR only make sense in a “authentification” (is that me ?) or “verification” (same person as in the other image ?) context

FAR and FRR are nicely explained here, but, there is nothing like an “imposter” or a “rejection” here, just correct or incorrect predictions

however, as long as you try to use that code, you should
build a “confusion matrix”, (for 10 persons, a 10x10 matrix, which you increase like conf[predicted, ground_truth] ++ for each prediction in your dataset), which will give you:

  • correctly identified persons on the diagonal
  • incorrectly identified as paul on the resp. row
  • paul incorrectly identified as someone else on the resp. col
3

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