Adaptive Biometric Systems

Recent Advances and Challenges

  • Ajita Rattani
  • Fabio Roli
  • Eric Granger

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-x
  2. C. Pagano, E. Granger, R. Sabourin, P. Tuveri, G. L. Marcialis, F. Roli
    Pages 9-34
  3. Norman Poh, Joseph Kittler, Ajita Rattani
    Pages 35-49
  4. Selma Belgacem, Clement Chatelain, Thierry Paquet
    Pages 51-72
  5. A. Das, R. Kunwar, U. Pal, M. A. Ferrer, M. Blumenstein
    Pages 73-96
  6. Zahid Akhtar, Amr Ahmed, Cigdem Eroglu Erdem, Gian Luca Foresti
    Pages 97-117
  7. Kamlesh Tiwari, Phalguni Gupta
    Pages 119-131
  8. Back Matter
    Pages 133-134

About this book

Introduction

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.

    Keywords

    Adaptive Biometrics Adaptive Pattern Recognition Computational Biometrics Intelligent Systems Pattern Recognition

    Editors and affiliations

    • Ajita Rattani
      • 1
    • Fabio Roli
      • 2
    • Eric Granger
      • 3
    1. 1.Michigan State UniversityEast LansingUSA
    2. 2.University of CagliariCagliariItaly
    3. 3.ETSMontréalCanada

    Bibliographic information

    • DOI https://doi.org/10.1007/978-3-319-24865-3
    • Copyright Information Springer International Publishing Switzerland 2015
    • Publisher Name Springer, Cham
    • eBook Packages Computer Science
    • Print ISBN 978-3-319-24863-9
    • Online ISBN 978-3-319-24865-3
    • Series Print ISSN 2191-6586
    • Series Online ISSN 2191-6594
    • About this book