Histogram equalization in SVM multimodal person verification

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dc.contributor.author	Farrús, Mireia
dc.contributor.author	Ejarque, Pascual
dc.contributor.author	Temko, Andrey
dc.contributor.author	Hernando, Javier
dc.date	2007
dc.identifier.citation	Farrús M, Ejarque P, Temko A, Hernando J. Histogram equalization in SVM multimodal person verification. In: Lee S-W, Li SZ, editors. Advances in Biometrics. International Conference, ICB 2007; 2007 Aug 27-29; Seoul, Korea. [place unknown]: Springer; 2007. p. 819-27. DOI: 10.1007/978-3-540-74549-5_86
dc.identifier.citation	http://dx.doi.org/10.1007/978-3-540-74549-5_86
dc.identifier.uri	http://hdl.handle.net/10230/30825
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	Springer
dc.relation	Lee S-W, Li SZ, editors. Advances in Biometrics. International Conference, ICB 2007; 2007 Aug 27-29; Seoul, Korea. [place unknown]: Springer; 2007. p. 819-27.
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	© Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-74549-5_86.
dc.subject	Speaker recognition
dc.subject	Multimodality
dc.subject	Fusion
dc.subject	Support vector machines
dc.subject	Histogram equalization
dc.subject	Prosody
dc.subject	Voice spectrum
dc.subject	Face
dc.title	Histogram equalization in SVM multimodal person verification
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/acceptedVersion
dc.description.abstract	Comunicació presentada a la International Conference on Biometrics (ICB) celebrada a Seoul (Korea) els dies 27 a 29 d'agost de 2007.
dc.description.abstract	It has been shown that prosody helps to improve voice spectrum based speaker recognition systems. Therefore, prosodic features can also be used in multimodal person verification in order to achieve better results. In this paper, a multimodal recognition system based on facial and vocal tract spectral features is improved by adding prosodic information. Matcher weighting method and support vector machines have been used as fusion techniques, and histogram equalization has been applied before SVM fusion as a normalization technique. The results show that the performance of a SVM multimodal verification system can be improved by using histogram equalization, especially when the equalization is applied to those scores giving the highest EER values.

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