Title
Error exponent analysis of person identification based on fusion of dependent/independent modalities: multiple hypothesis testing case
Abstract
In this paper we analyze the performance limits of multimodal biometric identification systems in the multiple hypothesis testing formulation. For the sake of tractability, we approximate the performance of the actual system by a set of pairwise binary tests. We point out that the attainable error exponent that can be achieved for such an approximation is limited by the worst pairwise Chernoff distance between alternative hypothesis prior models. We consider impact of the inter-modal dependencies on the attainable performance measure and demonstrate that, contrarily to the binary multimodal hypothesis testing framework, an expected performance gain from fusion of independent modalities does not any more play the role of lower bound on the gain one can expect from multimodal fusion.
Year
DOI
Venue
2008
10.1117/12.764849
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
hypothesis test,error exponent,multiple hypothesis testing,biometrics,lower bound
Modalities,Pairwise comparison,Alternative hypothesis,Upper and lower bounds,Multiple comparisons problem,Algorithm,Artificial intelligence,Biometrics,Mathematics,Statistical hypothesis testing,Binary number
Conference
Volume
ISSN
Citations 
6819
0277-786X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
O. Koval112815.81
Sviatoslav Voloshynovskiy277380.94
R. Villan3876.79
Thierry Pun43553290.95