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Handbook of Face Recognition

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Cover of 'Handbook of Face Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Face Recognition in Subspaces
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    Chapter 3 Face Subspace Learning
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    Chapter 4 Local Representation of Facial Features
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    Chapter 5 Face Alignment Models
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    Chapter 6 Morphable Models of Faces
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    Chapter 7 Illumination Modeling for Face Recognition
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    Chapter 8 Face Recognition Across Pose and Illumination
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    Chapter 9 Skin Color in Face Analysis
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    Chapter 10 Face Aging Modeling
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    Chapter 11 Face Detection
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    Chapter 12 Facial Landmark Localization
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    Chapter 13 Face Tracking and Recognition in Video
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    Chapter 14 Face Recognition at a Distance
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    Chapter 15 Face Recognition Using Near Infrared Images
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    Chapter 16 Multispectral Face Imaging and Analysis
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    Chapter 17 Face Recognition Using 3D Images
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    Chapter 18 Facial Action Tracking
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    Chapter 19 Facial Expression Recognition
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    Chapter 20 Face Synthesis
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    Chapter 21 Evaluation Methods in Face Recognition
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    Chapter 22 Dynamic Aspects of Face Processing in Humans
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    Chapter 23 Face Recognition by Humans and Machines
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    Chapter 24 Face Recognition Applications
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    Chapter 25 Large Scale Database Search
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    Chapter 26 Face Recognition in Forensic Science
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    Chapter 27 Privacy Protection and Face Recognition
Attention for Chapter 3: Face Subspace Learning
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Readers on

mendeley
12 Mendeley
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Chapter title
Face Subspace Learning
Chapter number 3
Book title
Handbook of Face Recognition
Published by
Springer, London, January 2011
DOI 10.1007/978-0-85729-932-1_3
Book ISBNs
978-0-85729-931-4, 978-0-85729-932-1
Authors

Bian, Wei, Tao, Dacheng, Wei Bian, Dacheng Tao

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Student > Master 3 25%
Professor 1 8%
Lecturer > Senior Lecturer 1 8%
Student > Bachelor 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 8 67%
Engineering 2 17%
Unknown 2 17%