Anzeige
Erschienen in:
2002 | OriginalPaper | Buchkapitel
An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems
verfasst von : Fabio Roli, Josef Kittler, Giorgio Fumera, Daniele Muntoni
Erschienen in: Multiple Classifier Systems
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.