Sciweavers

MCS
2002
Springer

An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems

13 years 9 months ago
An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems
In this paper, an experimental comparison between fixed and trained fusion rules for multimodal personal identity verification is reported. We focused on the behaviour of the considered fusion methods for ensembles of classifiers exhibiting significantly different performance, as this is one of the main characteristics of multimodal biometrics systems. The experiments were carried out on the XM2VTS database, using eight experts based on speech and face data. As fixed fusion methods, we considered the sum, majority voting, and order statistics based rules. The considered trained methods are the Behaviour Knowledge Space and the weighted averaging of classifiers outputs.
Fabio Roli, Josef Kittler, Giorgio Fumera, Daniele
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where MCS
Authors Fabio Roli, Josef Kittler, Giorgio Fumera, Daniele Muntoni
Comments (0)