Advertisement

© 2017

Deep Learning for Biometrics

  • Bir Bhanu
  • Ajay Kumar
  • The first dedicated work on advances in biometric identification capabilities using deep learning techniques

  • Covers a broad range of deep learning integrated biometric techniques, including face, fingerprint, iris, gait, template protection, and issues of security

  • Provides overviews of basic deep learning and biometrics topics for novices in these fields, complete with references for further reading

Book

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

Table of contents

  1. Front Matter
    Pages i-xxxi
  2. Deep Learning for Face Biometrics

    1. Front Matter
      Pages 1-1
    2. Yury Vizilter, Vladimir Gorbatsevich, Andrey Vorotnikov, Nikita Kostromov
      Pages 33-55
    3. Chenchen Zhu, Yutong Zheng, Khoa Luu, Marios Savvides
      Pages 57-79
  3. Deep Learning for Fingerprint, Fingervein and Iris Recognition

  4. Deep Learning for Soft Biometrics

  5. Deep Learning for Biometrics Security and Protection

    1. Front Matter
      Pages 257-257
    2. Rohit Kumar Pandey, Yingbo Zhou, Bhargava Urala Kota, Venu Govindaraju
      Pages 259-285
    3. Federico Pala, Bir Bhanu
      Pages 287-307
  6. Back Matter
    Pages 309-312

About this book

Introduction

This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined.

Topics and features:

  • Addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities
  • Revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition
  • Examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition
  • Discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition
  • Investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples
  • Presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories
  • Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning.

    Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

    Keywords

    Deep Learning Face Fingerprint Iris Gait Template Protection Anti-Spoofing Alexnet CNN RBM Biometrics Human Surveillance

    Editors and affiliations

    • Bir Bhanu
      • 1
    • Ajay Kumar
      • 2
    1. 1.University of CaliforniaRiversideUSA
    2. 2.Hong Kong Polytechnic UniversityHong KongChina

    About the editors

    Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video BioinformaticsDistributed Video Sensor Networks, and Human Recognition at a Distance in Video.

    Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

    Bibliographic information

    Industry Sectors
    Automotive
    Chemical Manufacturing
    Biotechnology
    IT & Software
    Telecommunications
    Law
    Consumer Packaged Goods
    Pharma
    Materials & Steel
    Finance, Business & Banking
    Electronics
    Energy, Utilities & Environment
    Aerospace
    Oil, Gas & Geosciences
    Engineering

    Reviews

    “This book, which covers different deep learning neural architectures for solving an extended set of problems in the area of biometrics, is sure to catch the attention of scholars and researchers working in the field.” (CK Raju, Computing Reviews, February, 2019)