Editors:
- The first book dedicated to the emerging field of adaptive biometric systems
- Describes the schemes and learning mechanisms involved in biometric system adaptation, and provides insight into the levels at which the process of adaptation can be performed
- Presents interdisciplinary coverage, bridging areas of computational intelligence, pattern recognition, machine learning, and signal processing
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
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.
Editors and Affiliations
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Michigan State University, East Lansing, USA
Ajita Rattani
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University of Cagliari, Cagliari, Italy
Fabio Roli
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ETS, Montréal, Canada
Eric Granger
About the editors
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.
Bibliographic Information
Book Title: Adaptive Biometric Systems
Book Subtitle: Recent Advances and Challenges
Editors: Ajita Rattani, Fabio Roli, Eric Granger
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-319-24865-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-24863-9Published: 04 November 2015
Softcover ISBN: 978-3-319-37222-8Published: 23 August 2016
eBook ISBN: 978-3-319-24865-3Published: 22 October 2015
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: X, 134
Number of Illustrations: 20 b/w illustrations, 24 illustrations in colour
Topics: Biometrics, Pattern Recognition, Signal, Image and Speech Processing, Artificial Intelligence