Kernel Learning Algorithms for Face Recognition

  • Jun-Bao Li
  • Shu-Chuan Chu
  • Jeng-Shyang Pan

Table of contents

  1. Front Matter
    Pages i-xv
  2. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 1-17
  3. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 19-47
  4. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 49-70
  5. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 71-99
  6. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 101-133
  7. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 135-157
  8. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 159-174
  9. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 175-188
  10. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 189-211
  11. Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
    Pages 213-223
  12. Back Matter
    Pages 225-225

About this book

Introduction

This book discusses the advanced kernel learning algorithms and its application on face recognition. The book focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. This authors aim to solve the parameter selection problems endured by kernel learning algorithms, and presents kernel optimization method with the data dependent kernel. This text extends the definition of data-dependent kernel and applies it to kernel optimization. Included within are algorithms of kernel based face recognition and the feasibility of the kernel based face recognition method.

Keywords

Analysis Based Face Recognition Kernel Clustering Kernel Construction Kernel Manifold Learning Kernel Neural Network Kernel Optimization Kernel learning Pattern recognition face recognition feature extraction

Authors and affiliations

  • Jun-Bao Li
    • 1
  • Shu-Chuan Chu
    • 2
  • Jeng-Shyang Pan
    • 3
  1. 1.Harbin Institute of TechnologyHarbinChina, People's Republic
  2. 2.Flinders University of South AustraliaBedford ParkAustralia
  3. 3.Department of Electronic EngineeringNational Kaohsiung University of AppliedSanmin DistrictTaiwan

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-0161-2
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Engineering
  • Print ISBN 978-1-4614-0160-5
  • Online ISBN 978-1-4614-0161-2
  • About this book