By Ajita Rattani, Fabio Roli, Eric Granger

ISBN-10: 3319248634

ISBN-13: 9783319248639

ISBN-10: 3319248650

ISBN-13: 9783319248653

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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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 [19] 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.

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Adaptive Biometric Systems: Recent Advances and Challenges by Ajita Rattani, Fabio Roli, Eric Granger

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