Advances in Face Image Analysis: Theory and Applications


by

Fadi Dornaika

DOI: 10.2174/97816810811061160101
eISBN: 978-1-68108-110-6, 2016
ISBN: 978-1-68108-111-3



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Indexed in: EBSCO.

Advances in Face Image Analysis: Theory and applications describes several approaches to facial image analysis and re...[view complete introduction]

Table of Contents

Foreword

- Pp. i

Denis Hamad

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Preface

- Pp. ii

Fadi Dornaika

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List of Contributors

- Pp. iii

Fadi Dornaika

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Facial Expression Classification Based on Convolutional Neural Networks

- Pp. 3-22 (20)

Wenyun Sun and Zhong Jin

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Sparsity Preserving Projection Based Constrained Graph Embedding and Its Application to Face Recognition

- Pp. 23-28 (6)

Libo Weng, Zhong Jin and Fadi Dornaika

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Face Recognition Using Exponential Local Discriminant Embedding

- Pp. 39-65 (27)

Alireza Bosaghzadeh and Fadi Dornaika

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Adaptive Locality Preserving Projections for Face Recognition

- Pp. 66-85 (20)

Fadi Dornaika and Ammar Assoum

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Face Recognition Using 3D Face Rectification

- Pp. 86-108 (23)

Alireza Bosaghzadeh, Mohammadali Doostari and Alireza Behrad

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3D Face Recognition

- Pp. 109-131 (23)

Alireza Behrad

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Model-Less 3D Face Pose Estimation

- Pp. 132-153 (22)

Fawzi Khattar, Fadi Dornaika and Ammar Assoum

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Efficient Deformable 3D Face Model Fitting to Monocular Images

- Pp. 154-180 (27)

Luis Unzueta, Waldir Pimenta, Jon Goenetxea, Luís Paulo Santos and Fadi Dornaika

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Face Detection Using the Theory of Evidence

- Pp. 181-216 (36)

Franck Luthon

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Fuzzy Discriminant Analysis: Considering the Fuzziness in Facial Age Feature Extraction

- Pp. 217-233 (17)

Shenglan Ben

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Facial Image-Based Age Estimation

- Pp. 234-250 (17)

Ammar Assoum and Jouhayna Harmouch

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Subject Index

- Pp. 251-254 (4)

Fadi Dornaika

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Foreword

Computer vision is one of the most active research fields in information technology, computer science and electrical engineering due to its numerous applications and major research challenges. Face image analysis constitutes an important field in computer vision and can be a key challenge in developing human-centered technologies. Face image analysis problems have been investigated in computer vision and Human Machine Interaction applications (e.g., identity verification, eye typing, emotion recognition, m-commerce). Making computers understand the contents of images taken by cameras is very challenging, and therefore the computer vision technology faces a lot of challenges. Differed from the biometric problems, e.g., finger-print or iris based recognition; face recognition inherently relies on the un-controlled environment and inevitably suffers from degrading factors such as illumination, expression, pose and age variations. Image-based age estimation is relatively a new research topic. Estimating human age automatically via facial image analysis has lots of potential real-world applications, such as human computer interaction and multimedia communication. This book presents the reader with cutting edge research in the domain of face image analysis. Besides, the book includes recent research works from different world research groups, providing a rich diversity of approaches to the face image analysis. The material covered in the eleven chapters of the book presents new advances on computer vision and pattern recognition approaches, as well as new knowledge and perspectives. The chapters, written by experts in their respective field, will make the reader acquainted with a number of topics and some trendy techniques used to tackle many problems related to face images. It is impressive to note that the editor and authors have tried to capture a wide and dynamic topic. I believe readers will not only learn from this book, but it will be of high reference value as well.

Prof. Denis Hamad
Université du Littoral Côte d’Opale,
Calais, France


Preface

Over the past two decades, many face image analysis problems have been investigated in computer vision and machine learning. The main idea and the driver of further research in this area are human-machine interaction and security applications. Face images and videos can represent an intuitive and non-intrusive channel for recognizing people, inferring their level of interest, and estimating their gaze in 3D. Although progress over the past decade has been impressive, there are significant obstacles to be overcome. It is not possible yet to design a face analysis system with a potential close to human performance. New computer vision and pattern recognition approaches need to be investigated. Face recognition as an essential problem in pattern recognition and social media computing, attracts many researchers for decades. For instance, face recognition became one of three identification methods used in e-passports and a biometric of choice for many other security applications. The E-Book "Advances in Face Image Analysis: Theory and Applications" is oriented to a wide audience including: i) researchers and professionals working in the fields of face image analysis; ii) the entire pattern recognition community interested in processing and extracting features from raw face images; and iii) technical experts as well as postgraduate students working on face images and their related concepts. One of the key benefits of this E-Book is that the readers will have access to novel research topics. The book contains eleven chapters that address several topics including automatic face detection, 3D face model fitting, robust face recognition, facial expression recognition, face image data embedding, model-less 3D face pose estimation and image-based age estimation. We would like to express our gratitude to all the contributing authors that have made this book a reality. We would also like to thank Prof. Denis Hamad for writing the foreword and Bentham Science Publishers for their support and efforts. A special thank goes to Dr. Ammar Assoum for providing the latex style file.

Editor Fadi Dornaika
University of the Basque Country Manuel Lardizabal, 1
20018 San Sebastián, Spain

List of Contributors

Editor(s):
Fadi Dornaika




Contributor(s):
Ammar Assoum
LaMA laboratory, Lebanese University
P.O. Box 826
Tripoli
Lebanon


Alireza Behrad
Department of Electrical and Electronic Engineering
Shahed university
Tehran-Qom Exp. Way, 3319118651
Tehran
Iran


Alireza Bosaghzadeh
University of the Basque Country
Manuel Lardizabal, 1, 20018
San Sebastian
Spain


Mohammadali Doostari
Department of Computer Engineering
Shahed university
Tehran-Qom Exp. Way, 3319118651
Tehran
Iran


Fadi Dornaika
University of the Basque Country
Manuel Lardizabal, 1, 20018
San Sebastian
Spain


Jon Goenetxea
Vicomtech-IK4, Paseo Mikeletegi, 57
Parque Tecnológico, 20009
Donostia
Spain


Jouhayna Harmouche
Faculty of Science, Lebanese University
P.O. Box 826
Tripoli
Lebanon


Zhong Jin
Nanjing University of Sciences and Technology
Nanjing, 210094
China


Fawzi Khattar
Faculty of Engineering, Lebanese University
P.O. Box 826
Tripoli
Lebanon


Franck Luthon
IUT de Bayonne Pays Basque, Université de Pau Pays d’Adour
2 allée du parc Montaury, 64600
Anglet
France


Waldir Pimenta
Departamento de Informática, University of Minho.
Campus de Gualtar, 4710-057
Braga
Portugal


Luis P. Santos
Departamento de Informática, University of Minho.
Campus de Gualtar, 4710-057
Braga
Portugal


Ben Shenglan
Nanjing University of Sciences and Technology
Nanjing, 210094
China


Wenyun Sun
Nanjing University of Sciences and Technology
Nanjing, 210094
China


Luis Unzueta
Vicomtech-IK4
Paseo Mikeletegi, 57, Parque Tecnológico, 20009
Donostia
Spain


Libo Weng
University of the Basque Country
Manuel Lardizabal, 1, 20018
San Sebastian
Spain
/
Nanjing University of Sciences and Technology
Nanjing, 210094
China




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