By Ajita Rattani, Fabio Roli, Eric Granger
This interdisciplinary quantity provides an in depth assessment of the newest advances and demanding situations final within the box of adaptive biometric platforms. A large diversity of concepts are supplied from a world collection of pre-eminent specialists, accrued jointly less than a unified taxonomy and designed to be appropriate to any development reputation method. positive aspects: provides an intensive advent to the idea that of adaptive biometric structures; stories platforms for adaptive face popularity that practice self-updating of facial versions utilizing operational (unlabeled) info; describes a singular semi-supervised education technique referred to as fusion-based co-training; examines the characterization and popularity of human gestures in video clips; discusses a variety of studying suggestions that may be utilized to construct an adaptive biometric process; investigates strategies for dealing with temporal variance in facial biometrics because of getting older; proposes a score-level fusion scheme for an adaptive multimodal biometric system.
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Additional resources for Adaptive Biometric Systems: Recent Advances and Challenges
31(2), 210–227 (2009) 7. : A survey of face recognition techniques. J. Inf. Process. Syst. 5(2), 41–68 (2009) 8. : Handbook of Face Recognition, 2nd edn. Springer Publishing Company, Incorporated (2011) 9. : Adaptive biometric system based on template update procedures. D. thesis. University of Cagliari, Italy (2010) 10. : A framework for generating data to simulate changing environments. In: Proceedings of the 25th IASTED International Multi-Conference: Artificial Intelligence And Applications, pp.
The BANCA database and evaluation protocol. In: International Conference Audio- and Video-Based Biometric Person Authentication (AVBPA) (2003) 3. : Combining labeled and unlabeled data with co-training.
To standardize the experimental protocol, each database is separated into six different batches for all individuals. These scenarios are summarized at the end of Sect. 1. 1 Multi-Modal Dipartimento di Ingegneria Elettrica Ed Elettronica The multi-modal Dipartimento di Ingegneria Elettrica ed Elettronica4 (DIEE) dataset  regroups face and fingerprint captures of 49 individuals. In this study, only facial captures are considered. For each individual, 60 facial captures have been acquired over 6 sessions at least 3 weeks apart, with 10 captures per session.
Adaptive Biometric Systems: Recent Advances and Challenges by Ajita Rattani, Fabio Roli, Eric Granger