The Community for Technology Leaders
RSS Icon
Issue No.01 - Jan.-Mar. (2013 vol.12)
pp: 79-87
The Mobile Biometrics (MoBio) project combines real-time face and voice verification for better security of personal data stored on, or accessible from, a mobile platform.
speech recognition, data privacy, face recognition, mobile computing, security of data, personal data security, mobile platform, MoBio project, mobile biometrics project, real-time face verification, real-time voice verification, Face recognition, Mobile communication, Shape analysis, Biometrics, Pervasive computing, Mobile computing, Mobile handsets, Network security, MoBio, mobile biometrics, face verification, voice authentication, pervasive computing
P. Tresadern, T. F. Cootes, N. Poh, P. Matejka, A. Hadid, Christophe Levy, C. McCool, S. Marcel, "Mobile Biometrics: Combined Face and Voice Verification for a Mobile Platform", IEEE Pervasive Computing, vol.12, no. 1, pp. 79-87, Jan.-Mar. 2013, doi:10.1109/MPRV.2012.54
1. G. Chetty and M. Wagner, “Multi-Level Liveness Verification for Face-Voice Biometric Authentication,” Proc. Biometric Symp., IEEE, 2006; doi:10.1109/BCC.2006.4341615.
2. A.B.J. Teoh, S.A. Samad, and A. Hussain, “A Face and Speech Biometric Verification System Using a Simple Bayesian Structure,” J. Information and Science Eng., vol. 21, 2005, pp. 1121–1137.
3. M. Pietikainen et al., Computer Vision Using Local Binary Patterns, Springer, 2011.
4. P. Viola and M.J. Jones, “Robust Real-Time Face Detection,” Int'l J. Computer Vision, vol. 57, no. 2, 2004, pp. 137–154.
5. C. Atanasoaei, C. McCool,, and S. Marcel, “A Principled Approach to Remove False Alarms by Modelling the Context of a Face Detector,” Proc. British Machine Vision Conf., BMVA Press, 2010; doi:10.5244/C.24.17.
6. P.A. Tresadern, M.C. Ionita, and T.F. Cootes, “Real-Time Facial Feature Tracking on a Mobile Device,” Int'l J. Computer Vision, vol. 96, no. 3, 2011, pp. 280–289.
7. T. Ahonen et al., “Recognition of Blurred Faces Using Local Phase Quantization,” Proc. IEEE Int'l Conf. Pattern Recognition, IEEE, 2008; doi:10.1109/ICPR.2008.4761847.
8. C.H. Chan and J. Kittler, “Sparse Representation of (Multiscale) Histograms for Face Recognition Robust to Registration and Illumination Problems,” Proc. Int'l Conf. Image Processing, IEEE, 2010, pp. 2441–2444.
9. A. Roy, M. Magimai-Doss, and S. Marcel, “Phoneme Recognition Using Boosted Binary Features,” Proc. IEEE Int'l Conf. Acoustics, Speech and Signal Processing, IEEE, 2011, pp. 4868–4871.
10. O. Glembek et al., “Simplification and Optimization of i-Vector Extraction,” Proc. IEEE Int'l Conf. Acoustics, Speech and Signal Processing, IEEE, 2011, pp. 4516–4519.
11. A. Larcher et al., “Decoupling Session Variability Modelling and Speaker Characterisation,” Proc. 11th Ann. Conf. Int'l Speech Communication Assoc. (Interspeech 10), ISCA, 2010, pp. 2314–2317.
12. A. Roy, M. Magimai-Doss, and S. Marcel, “A Fast Parts-Based Approach to Speaker Verification Using Boosted Slice Classifiers,” IEEE Trans. Information Forensics and Security, vol. 7, no. 1, 2011; doi:10.1109/TIFS.2011.2166387.
13. N. Poh et al., “Model and Score Adaptation for Biometric Systems: Coping with Device Interoperability and Changing Acquisition Conditions,” Proc. 2010 20th Int'l Conf. Pattern Recognition, IEEE, 2010, pp. 1229–1232.
14. N. Poh, J. Kittler, and T. Bourlai, “Quality-Based Score Normalization with Device Qualitative Information for Multimodal Biometric Fusion,” IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 3, 2010, pp. 539–554.
15. S. Marcel et al., “On the Results of the First Mobile Biometry (MoBio) Face and Speaker Verification Evaluation,” Proc. 20th Int'l Conf. Recognizing Patterns in Signals, Speech, Images, and Videos (ICPR 10), Springer, 2011, pp. 210–225.
10 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool