Facial Kinship Verification

A Machine Learning Approach

  • Haibin Yan
  • Jiwen Lu

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-x
  2. Haibin Yan, Jiwen Lu
    Pages 1-5
  3. Haibin Yan, Jiwen Lu
    Pages 7-36
  4. Haibin Yan, Jiwen Lu
    Pages 37-62
  5. Haibin Yan, Jiwen Lu
    Pages 63-80
  6. Haibin Yan, Jiwen Lu
    Pages 81-82

About this book

Introduction

This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification.

Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.

Keywords

Kinship Verification Feature Learning Metric Learning Face Analysis Biometrics

Authors and affiliations

  • Haibin Yan
    • 1
  • Jiwen Lu
    • 2
  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Tsinghua UniversityBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-4484-7
  • Copyright Information The Author(s) 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-10-4483-0
  • Online ISBN 978-981-10-4484-7
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • About this book
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