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Advances in Face Detection and Facial Image Analysis

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Cover of 'Advances in Face Detection and Facial Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 A Deep Learning Approach to Joint Face Detection and Segmentation
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    Chapter 2 Face Detection Coupling Texture, Color and Depth Data
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    Chapter 3 Lighting Estimation and Adjustment for Facial Images
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    Chapter 4 Advances, Challenges, and Opportunities in Automatic Facial Expression Recognition
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    Chapter 5 Exaggeration Quantified: An Intensity-Based Analysis of Posed Facial Expressions
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    Chapter 6 Method of Modelling Facial Action Units Using Partial Differential Equations
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    Chapter 7 Trends in Machine and Human Face Recognition
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    Chapter 8 Labeled Faces in the Wild: A Survey
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    Chapter 9 Reference-Based Pose-Robust Face Recognition
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    Chapter 10 On Frame Selection for Video Face Recognition
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    Chapter 11 Modeling of Facial Wrinkles for Applications in Computer Vision
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    Chapter 12 Communication-Aid System Using Eye-Gaze and Blink Information
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    Chapter 13 The Utility of Facial Analysis Algorithms in Detecting Melancholia
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    Chapter 14 Visual Speech Feature Representations: Recent Advances
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    Chapter 15 Extended Eye Landmarks Detection for Emerging Applications
Attention for Chapter 6: Method of Modelling Facial Action Units Using Partial Differential Equations
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Citations

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Chapter title
Method of Modelling Facial Action Units Using Partial Differential Equations
Chapter number 6
Book title
Advances in Face Detection and Facial Image Analysis
Published by
Springer International Publishing, April 2016
DOI 10.1007/978-3-319-25958-1_6
Book ISBNs
978-3-31-925956-7, 978-3-31-925958-1
Authors

Hassan Ugail, Nur Baini Ismail

Editors

Michal Kawulok, M. Emre Celebi, Bogdan Smolka

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 33%
Lecturer 2 33%
Student > Postgraduate 1 17%
Student > Doctoral Student 1 17%
Readers by discipline Count As %
Computer Science 3 50%
Mathematics 2 33%
Unknown 1 17%

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