Open world face recognition with credibility and confidence measures

Authors:
Fayin Li;Harry Wechsler
Affiliations:
Department of Computer Science, George Mason University, Fairfax, VA;Department of Computer Science, George Mason University, Fairfax, VA
Venue:
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Year:
2003

Citing 5
Cited 0

An introduction to Kolmogorov complexity and its applications (2nd ed.)

An introduction to Kolmogorov complexity and its applications (2nd ed.)
Ridge Regression Confidence Machine

ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Machine-Learning Applications of Algorithmic Randomness

ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Learning by transduction

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a novel framework for the Open World face recognition problem, where one has to provide for the Reject option. Based upon algorithmic randomness and transduction, a particular form of induction, we describe the TCM-kNN (Transduction Confidence Machine - kNearest Neighbor) algorithm for Open World face recognition. The algorithm proposed performs much better than PCA and is comparable with Fisherfaces. In addition to recognition and rejection, the algorithm can assign credibility ("likelihood") and confidence ("lack of ambiguity") measures with the identification decisions taken.