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Biometrics Research Lab. /ATVS Universidad Politecnica de Madrid atvs.diac.upm.es

Towards a “Chimeric” Super-Database involving XM2VTS, MCYT and BIOMET databases. Javier Ortega-Garcia, PhD. Biometrics Research Lab. /ATVS Universidad Politecnica de Madrid www.atvs.diac.upm.es. Lack of large-scale (100s) fully multimodal databases

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Biometrics Research Lab. /ATVS Universidad Politecnica de Madrid atvs.diac.upm.es

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  1. Towards a “Chimeric” Super-Database involving XM2VTS, MCYT and BIOMET databases Javier Ortega-Garcia, PhD Biometrics Research Lab. /ATVS Universidad Politecnica de Madrid www.atvs.diac.upm.es

  2. Lack of large-scale (100s) fully multimodal databases Ever-growing importance of multimodal biometric research No common evaluation corpus and framework «Construction» (definition/design, organization, protocol, production…) of a chimeric (imaginary individuals) super-database Exploiting 3 large-scale existing databases: XM2VTS, MCYT, BIOMET Most of the groups integrated under COST-275 Motivation and Needs

  3. University of Surrey + IDIAP 295 individuals, 4 sessions, 2 shots per session High quality digital video (+ audio) sequences 1st shot: Frontal image + speaking 3 common sentences 2nd shot: Head movemets Clearly stablished protocol: training, evaluation (thresholding), testing Strong points: large-scale, multi-session, face recognition-oriented, 3D face analysis, face profiling, lip movements, audio/video sync. Lacks: less speech, common read sentences; no other modalities XM2VTS Database

  4. Spanish Universities (National Project): Technical Univ. of Madrid + School of EE at Mataró (Barcelona) + Univ. of Basque Country + Univ. of Valladolid. 332 individuals, 1 session, distributed collection (4 groups) On-line signature: graphics tablet-based, high quality; each individual: 25 authentic (in separate sets of 5) and 25 high-skilled forgeries. Fingerprints: 10 fingers per individual, 12 samples per sensor, 2 sensors (capacitive and optical), 3 levels of core position control in acquisition. Strong points: large-scale, multi-site, written samples of signatures (valid for off-line purposes), inter-sensor variabilty of fingerprints, manual labelling of fingerprint subset (75 individuals, 9,000 samples) quality (14 quality categories) Lacks: no multi-session (multisession subset currently under design); no other modalities MCYT Database

  5. French GET (ENST, INT, EURECOM) 131 individuals, 3 sessions Modalities: Face, speech, on-line signature, fingerprints, hand shape Hand shape: 1 image of left hand (optical scanner) Fingerprints: index+middle fingers, right hand, 1 sample On-line signature: 5 genuine + 5 (shape-based) forgeries Digital video sequence: speech (french, digit-strings + 12 sentences) + face movements Strong points: multimodality, multi-session, also face images (still) with infrared illumination, 3D face acquisition Lacks: not so large-scale, no unified multimodal acquisition scenario BIOMET Database

  6. XM2VTS: large, multisession, face rec. MCYT: large, single-session, on-line signature and fingerprints BIOMET: medium, multisession, multimodal, hand geometry Speech? Using of English XM2VTS, French BIOMET and Spanish AHUMADA; read short sentences and digit strings About 100 multimodal chimeric individuals Data oriented to basic biometric recognition Controled intravariabiltiy problems (still frontal faces, centered fingerprints, …) Production and disseminations costs (COST-275, 3 k€) Distribution issues (COST, ELDA, …) Design Key Issues (preliminary)

  7. Super-database proposal: Rome (Nov-02) Exact description of each database (Feb-03) Definition of super-database (March-03) Def. of a common assessment protocol (Apr-03) Discussion about definition and protocol (May-03) Structure, organization, indexing of data (June-03) Production (July-03) Dissemination efforts (> July 2003) Workprogramme

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