Adaptive Biometric Systems : Recent Advances and Challenges

Ajita Rattani

ISBN 10: 3319248634 / ISBN 13: 9783319248639

Editore: Springer International Publishing, 2015

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - This interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system.

Codice articolo 9783319248639

Dati bibliografici

• Titolo: Adaptive Biometric Systems : Recent Advances and Challenges
• Editore: Springer International Publishing
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 3319248634
• ISBN 13: 9783319248639
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 14 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 14 millimetri di profondità
• Peso: 389 grammi

Descrizione articolo

Riassunto

This interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system.

Informazioni sull?autore

Dr. Ajita Rattani is a post-doctoral fellow in the Integrated Pattern Recognition and Biometrics (i-PRoBe) lab at Michigan State University, East Lansing, MI, USA. Dr. Fabio Roli is a professor of computer engineering and the Director of the Pattern Recognition and Applications (PRA) lab at the University of Cagliari, Italy. Dr. Eric Granger is a professor in the Department of Automated Manufacturing Engineering and the Director of the Laboratory for Imagery, Vision and Artificial Intelligence at the École de technologie supérieure (ÉTS), Montréal, QC, Canada.