The multiscenario multienvironment biosecure multimodal database (BMDB) - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Pattern Analysis and Machine Intelligence Année : 2010

The multiscenario multienvironment biosecure multimodal database (BMDB)

Résumé

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1 over the Internet, 2 in an office environment with desktop PC, and 3 in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008

Dates et versions

hal-01333456 , version 1 (17-06-2016)

Identifiants

Citer

Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R. Freire, et al.. The multiscenario multienvironment biosecure multimodal database (BMDB). IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32 (6), pp.1097 - 1111. ⟨10.1109/TPAMI.2009.76⟩. ⟨hal-01333456⟩
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