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 TecnolĂłgico, 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 TecnolĂłgico, 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