Combination of Experts by Classifiers in Similarity Score Spaces
The combination of different experts is largely used to improve the performance of a pattern recognition system. In the case of experts whose output is a similarity score, different methods had been developed. In this paper, the combination is performed by building a similarity score space made up of the scores produced by the experts, and training a classifier into it. Different techniques based on the use of classifiers trained on the similarity score space are proposed and compared. In particular, they are used in the framework of Dynamic Score Selection mechanisms, recently proposed by the authors. Reported results on two biometric datasets show the effectiveness of the proposed approach.