The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
The NIST HumanID evaluation framework
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Combining Matching Scores in Identification Model
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Predicting fingerprint biometrics performance from a small gallery
Pattern Recognition Letters
Statistical Performance Evaluation of Biometric Authentication Systems Using Random Effects Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of biometric technology based on hand shape
Pattern Recognition
Fusion in Multibiometric Identification Systems: What about the Missing Data?
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Asymptotic biometric analysis for large gallery sizes
IEEE Transactions on Information Forensics and Security
Robust fusion: extreme value theory for recognition score normalization
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
An integrated prediction model for biometrics
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Performance evaluation and prediction for 3d ear recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Evaluation of biometric identification in open systems
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Face recognition for web-scale datasets
Computer Vision and Image Understanding
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We present new binomial models of open- and closed-set identification recognition performance, giving formulae for identification and false match rates as functions of database size, match rank and operating threshold. We compare these with previously published models and with results from face recognition trials on populations of size 4 104. We note verification to be a special case of open-set identification and relate area under the receiver operating characteristic to closed-set identification. We find the binomial model approximates performance at low false match rates but underestimates identification rates on closed sets. We implicate the binomial iid assumption, but show conditioning and score transformation methods that ameliorate this.