Adaptive Biometric Systems: Recent Advances and Challenges - Couverture rigide

Couverture rigide

ISBN 10 : 3319248634 ISBN 13 : 9783319248639

Editeur : Springer International Publishing AG, 2015

Synopsis

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.

A propos du livre

À propos de l'auteur

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.

À propos de la quatrième de couverture

This timely and 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.

Topics and features:

• Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges
  
• 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

This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate

students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments.

Détails de l'édition

• Éditeur: Springer International Publishing AG
• Date d'édition: 2015
• Langue: anglais
• ISBN 10: 3319248634
• ISBN 13: 9783319248639
• Reliure: Relié
• Numéro d'édition: 1
• Nombre de pages: 134
• Éditeur: Rattani Ajita, Roli Fabio, Granger Eric
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne