Bi-Modal Person Recognition on a Mobile Phone: using mobile phone data

Chris Mccool (1) , Sébastien Marcel , Abdenour Hadid (2) , Matti Pietikainen (3) , Pavel Matějka (4) , Jaň Černocký (5) , Norman Poh (6) , Josef Kittler (7) , Anthony Larcher (8) , Christophe Levy (8) , Driss Matrouf (8) , Jean-François Bonastre (8) , Phil Tresadern (9) , Timothy Cootes (9)

1 IDIAP Research Institute
2 University of Oulu
3 MVG - Machine Vision Group
4 Phonexia s. r. o. (Phonexia s. r. o.)
5 BUT - Brno University of Technology [Brno]
6 CVSSP - Centre for Vision, Speech and Signal Processing
7 UNIS - University of Surrey
8 LIA - Laboratoire Informatique d'Avignon
9 University of Manchester [Manchester]

This paper presents a novel fully automatic bi-modal, face and speaker, recognition system which runs in real-time on a mobile phone. The implemented system runs in real-time on a Nokia N900 and demonstrates the feasibility of performing both automatic face and speaker recognition on a mobile phone. We evaluate this recognition system on a novel publicly-available mobile phone database and provide a well defined evaluation protocol. This database was captured almost exclusively using mobile phones and aims to improve research into deploying biometric techniques to mobile devices. We show, on this mobile phone database, that face and speaker recognition can be performed in a mobile environment and using score fusion can improve the performance by more than 25% in terms of error rates.

Mots clés: bi-modal authentication; mobile biometrics; speaker recognition; face recognition

Domaines: Intelligence artificielle [cs.AI]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Chris Mccool, Sébastien Marcel, Abdenour Hadid, Matti Pietikainen, Pavel Matějka, et al.. Bi-Modal Person Recognition on a Mobile Phone: using mobile phone data. IEEE International Conference on Multimedia and Expo (ICME), Jul 2012, Melbourne, Australia. ⟨10.1109/ICMEW.2012.116⟩. ⟨hal-01927787⟩