Advances in Face Image Analysis: Techniques and Technologies

Advances in Face Image Analysis: Techniques and Technologies

Copyright: © 2011 |Pages: 404

ISBN13: 9781615209910|ISBN10: 1615209913|EISBN13: 9781615209927

DOI: 10.4018/978-1-61520-991-0

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Zhang, Yu-Jin, editor. Advances in Face Image Analysis: Techniques and Technologies. IGI Global, 2011. https://doi.org/10.4018/978-1-61520-991-0

APA

Zhang, Y. (Ed.). (2011). Advances in Face Image Analysis: Techniques and Technologies. IGI Global. https://doi.org/10.4018/978-1-61520-991-0

Chicago

Zhang, Yu-Jin, ed. Advances in Face Image Analysis: Techniques and Technologies. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61520-991-0

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Video and image analysis of the human face provides a wealth of information about the individual, , including age, behavior, health and profession. With research continually being conducted into multiple applications of this field, a comprehensive and detailed volume of the new advancements of face image analysis is in demand.

Advances in Face Image Analysis: Techniques and Technologies fulfills this need, reviewing and surveying new forward-thinking research and development in face image analysis technologies. With more than 30 leading experts from around the world providing comprehensive coverage of various branches of face image analysis, this book is a valuable asset for students, researchers and practitioners engaged in the study, research and development of face image analysis techniques.

Table of Contents

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Front Materials

Title Page

Copyright Page

Preface

Acknowledgment

Chapters

Introduction and Background

Chapter 1

Face, Image, and Analysis (pages 1-15)

Yu-Jin Zhang, Yu-Jin Zhang, J.L. Molina, R. Giordano, J. Bromley

Face image analysis, consisting of automatic investigation of images of (human) faces, is a hot research topic and a fruitful field. This introductory chapter discusses several aspects of the history and scope of face image analysis...

Chapter 2

Face Searching in Large Databases (pages 16-41)

Maria De Marsico, Maria De Marsico, Michele Nappi, Michele Nappi, Daniel Riccio, Sergio Vitulano

Both government agencies and private companies are investing significant resources to improve local/remote access security. Badge or password-based procedures have proven to be too vulnerable, while biometric research has...

Facial Feature Extraction

Chapter 3

A Review of Facial Feature Detection Algorithms (pages 42-61)

Stylianos Asteriadis, Nikos Nikolaidis, Nikos Nikolaidis, Ioannis Pitas, Ioannis Pitas

Facial feature localization is an important task in numerous applications of face image analysis that include face recognition and verification, facial expression recognition, driver‘s alertness estimation, head pose estimation etc....

Chapter 4

Gabor and Log-Gabor Wavelet for Face Recognition (pages 62-81)

M. Ashraful Amin, Hong Yan, Hong Yan

In practice Gabor wavelet is often applied to extract relevant features from a facial image. This wavelet is constructed using filters of multiple scales and orientations. Based on Gabor’s theory of communication, two methods are...

Chapter 5

Efficient Face Retrieval Based on Bag of Facial Features (pages 82-96)

Yuanjia Du, Yuanjia Du, Ling Shao, P. Archambeau, S. Erpicum, M. Pirotton

In this chapter, the authors present an efficient retrieval technique for human face images based on bag of facial features. A visual vocabulary is built beforehand using an invariant descriptor computed on detected image regions....

Feature Dimensionality Reduction

Chapter 6

Feature Selection in High Dimension (pages 97-119)

Sébastien Gadat

Variable selection for classification is a crucial paradigm in image analysis. Indeed, images are generally described by a large amount of features (pixels, edges …) although it is difficult to obtain a sufficiently large number of...

Chapter 7

Transform Based Feature Extraction and Dimensionality Reduction Techniques (pages 120-136)

V. Jadhav Dattatray, Dattatray V. Jadhav, Raghunath S. Holambe, S. Holambe Raghunath

Various changes in illumination, expression, viewpoint, and plane rotation present challenges to face recognition. Low dimensional feature representation with enhanced discrimination power is of paramount importance to face...

Chapter 8

FastNMF: Efficient NMF Algorithm for Reducing Feature Dimension (pages 137-163)

Le Li, Yu-Jin Zhang

Non-negative matrix factorization (NMF) is a more and more popular method for non-negative dimensionality reduction and feature extraction of non-negative data, especially face images. Currently no NMF algorithm holds not only...

Face Recognition

Chapter 9

Sparse Representation for View-Based Face Recognition (pages 164-177)

Imran Naseem, Imran Naseem, Roberto Togneri, Roberto Togneri, Mohammed Bennamoun

In this chapter, the authors discuss the problem of face recognition using sparse representation classification (SRC). The SRC classifier has recently emerged as one of the latest paradigm in the context of view-based face...

Chapter 10

Probabilistic Methods for Face Registration and Recognition (pages 178-197)

Peng Li, Simon J. D. Prince

In this chapter the authors review probabilistic approaches to face recognition and present extended treatment of one particular approach. Here, the face image is decomposed into an additive sum of two parts: a deterministic...

Chapter 11

Discriminant Learning Using Training Space Partitioning (pages 198-216)

Marios Kyperoundtas, Marios Kyperountas, Anastasios Tefas, Ioannis Pitas

Large training databases introduce a level of complexity that often degrades the classification performance of face recognition methods. In this chapter, an overview of various approaches that are employed in order to overcome this...

Facial Expression Classification

Chapter 12

From Face to Facial Expression (pages 217-238)

Zakia Hammal

This chapter addresses recent advances in computer vision for facial expression classification. The authors present the different processing steps of the problem of automatic facial expression recognition. They describe the advances...

Chapter 13

Facial Expression Analysis by Machine Learning (pages 239-258)

Siu-Yeung Cho, Teik-Toe Teoh, Yok-Yen Nguwi

Facial expression recognition is a challenging task. A facial expression is formed by contracting or relaxing different facial muscles on human face that results in temporally deformed facial features like wide-open mouth, raising...

Chapter 14

Subtle Facial Expression Recognition in Still Images and Videos (pages 259-278)

Fadi Dornaika, Fadi Dornaika, Bogdan Raducanu, Bogdan Raducanu

This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an...

Invariance Techniques

Chapter 15

Photometric Normalization Techniques for Illumination Invariance (pages 279-300)

Vitomir Štruc, Nikola Pavešic

Face recognition technology has come a long way since its beginnings in the previous century. Due to its countless application possibilities, it has attracted the interest of research groups from universities and companies around the...

Chapter 16

Pose and Illumination Invariance with Compound Image Transforms (pages 301-315)

Lior Shamir, Lior Shamir

While current face recognition algorithms have provided convincing performance on frontal face poses, recognition is far less effective when the pose and illumination conditions vary. Here the authors show how compound image...

Chapter 17

Configural Processing Hypothesis and Face-Inversion Effect (pages 316-333)

Sam S. Rakover

Perception and recognition of faces presented upright are better than Perception and recognition of faces presented inverted. The difference between upright and inverted orientations is greater in face recognition than in non-face...

Back Materials

Compilation of References

About the Contributors

Index

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