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Proceedings Paper

Error exponent analysis of person identification based on fusion of dependent/independent modalities: multiple hypothesis testing case
Author(s): Oleksiy Koval; Sviatoslav Voloshynovskiy; Renato Villan; Thierry Pun
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Paper 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.

Paper Details

Date Published: 18 March 2008
PDF: 8 pages
Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190P (18 March 2008); doi: 10.1117/12.764849
Show Author Affiliations
Oleksiy Koval, Univ. of Geneva (Switzerland)
Sviatoslav Voloshynovskiy, Univ. of Geneva (Switzerland)
Renato Villan, Univ. of Geneva (Switzerland)
Thierry Pun, Univ. of Geneva (Switzerland)


Published in SPIE Proceedings Vol. 6819:
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
Edward J. Delp; Ping Wah Wong; Jana Dittmann; Nasir D. Memon, Editor(s)

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