Face-antispoofing expt. using image-quality measures and LDA, on ReplayAttack database

Outputs for block Score_Analyzer

dev_eer 0.0633333
dev_eer_threshold 0.0235956
dev_far 0.06
dev_frr 0.0666667
test_far 0.055
test_frr 0.15
test_hter 0.1025
dev_numNegatives 300
dev_numPositives 60
test_numNegatives 400
test_numPositives 80
dev_scoreDistribution
test_scoreDistribution
dev_roc
test_roc
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The experiment uses 18 image-quality measures (IQM). These IQM are computed for each frame of the input video, and the feature-sets are used to construct a 2-class classifier via Linear Discriminant Analysis (LDA).

The image-quality measures used here form a subset of the measures proposed by Galbally et al:

@INPROCEEDINGS{Galbally_IEEEICPR2014_2014,
  author = {Galbally, Javier and Marcel, S{\'{e}}bastien},
  title = {Face Anti-spoofing Based on General Image Quality Assessment},
  booktitle = {Proceedings of the 22nd International Conference on Pattern Recognition},
  month = aug,
  year = {2014},
}

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This experiment is attested.
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