PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Why Do Multi-Stream, Multi-Band and Multi-Modal Approaches Work on Biometric User Authentication Tasks?
Norman Poh and Samy Bengio
In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004), 17-21 May 2004, Montreal.

Abstract

Multi-band, multi-stream and multi-modal approaches have proven to be very successful both in experiments and in real-life applications, among which speech recognition and biometric authentication are of particular interest here. However, there is a lack of a theoretical study to justify why and how they work, when one combines the streams at the feature or classifier score levels. In this paper, we attempt to cast a light onto the latter subject. Our findings suggest that combining several experts using the mean operator, Multi-Layer-Perceptrons and Support Vector Machines always perform better than the average performance of the underlying experts. Furthermore, in practice, most combined experts using the methods mentioned above perform better than the best underlying expert.

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EPrint Type:Conference or Workshop Item (Paper)
Additional Information:biometric authentication fusion
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Multimodal Integration
ID Code:819
Deposited By:Norman Poh
Deposited On:01 January 2005