PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Score Fusion by Maximizing the Area Under the ROC Curve
M. Villegas and Roberto Paredes
In: 4th Iberian Conference on Pattern Recognition and Image Analysis, Portugal(2009).


Information fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the parameters of a score fusion model based on maximizing an index related to the Area Under the ROC Curve. This approach has the convenience that the fusion parameters are learned without having to specify the client and impostor priors or the costs for the different errors. Empirical results on several datasets show the effectiveness of the proposed approach.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5672
Deposited By:Alfons Juan
Deposited On:08 March 2010