Face Processing: Advanced Modeling and Methods / Edition 1

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Overview

Major strides have been made in face processing in the last ten years due to the availability of capable technologies. Editors Wenyi Zhao and Rama Chellappa have assembled over thirty-five leading experts in image processing, pattern recognition, neural network and learning, computer vision, graphics and psychology to create a compendium on current face processing methods, techniques, and applications.

Presented in three sections, this reference covers the entire spectrum of face processing from face detection to feature extraction to recognition. The first section covers the basic aspects of face processing from human to computer. The second discusses face modeling from computational and physiological points of view. The third tackles the advanced methods including robust methods that handle illumination, pose and expression and industrial applications. The extensive detail provided by the contributors of this volume makes this a need-to-own book for anyone in the industry or academia involved in image processing.

KEY FEATURES
• All types of processing examined including detection, tracking, modeling, analysis and synthesis
• Essential to technology involving smart cards, internet access, security, and video game design
• Guided tour and surveys of eigenfaces, statistical evaluation of face recognition, and 3D face modeling
• Over 150 educational and informative images illustrating face processing in action

Wenyi Zhao received a doctoral degree in Electrical Engineering in 2000from the University of Maryland. His Ph.D. research was focused on robust face recognition. He studied electronic engineering with focus on image processing hardware at Tsinghua University, Beijing for his B.E. degree in 1990; electrical engineering with focus on computer vision applications at University of Virginia for his M.S. degree in 1995. He joined the Vision Technologies Laboratory of Sarnoff Corporation in 2000. He has contributed more than 35 book chapters, peer-reviewed journal and conference articles. He is a recipient of the best industry related paper award at the 17th International Conference on Pattern Recognition, 2004.

Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from the Indian Institute of Science, Bangalore, in 1977. He received the M.S.E.E. and Ph.D. Degrees in electrical engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. He is a professor of Electrical and Computer Engineering and an Affliate Professor of Computer Science. Recently, he has been named the Minta Martin Professor of Engineering in the Clark School of Engineering. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent member). He is a fellow of IEEE and IAPR. Dr. Chellappa has served as an associate editor of the IEEE Transactions on Signal Processing, Pattern Analysis and Machine Intelligence, Image Processing, and Neural Networks. He was co-Editor-in-Chief of Graphical models and Image Processing. He was Editor-in-Chief of IEEE Transactions on Pattern Analysis and Machine Intelligence during 2001 to 2004.

Major strides have been made in face processing in the last ten years due to the fast growing need for security in various locations around the globe. A human eye can discern the details of a specific face with relative ease. It is this level of detail that researchers are striving to create with ever evolving computer technologies that will become our perfect mechanical eyes. The difficulty that confronts researchers stems from turning a 3D object into a 2D image. That subject is covered in depth from several different perspectives in this volume.

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Product Details

  • ISBN-13: 9780120884520
  • Publisher: Elsevier Science
  • Publication date: 12/28/2005
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 768
  • Product dimensions: 6.20 (w) x 9.00 (h) x 1.50 (d)

Table of Contents

Preface
PART I: THE BASICS
Chapter 1: A Guided Tour for Face Processing
Chapter 2: Eigenface and Beyond
Chapter 3: Statistical Evaluation of Face Recognition Systems

PART II: FACE MODELING
Chapter 4: 3D Morphable Face Model: A Unified Approach for Analysis and Synthesis of Images
Chapter 5: Expression-Invariant Three-Dimensional Face Recognition
Chapter 6: 3D Face Modeling from Monocular Video Sequences
Chapter 7: Face Modeling by Information Maximization
Chapter 8: Face Recognition by Human
Chapter 9: Predicting Face Recognition Success for Humans
Chapter 10: Distributed Representation of Faces and Objects

PART III: ADVANCED METHODS
Chapter 11: On the Effect of Illumination and Face Recognition
Chapter 12: Modeling Illumination Variation with Spherical Harmonics
Chapter 13: Multi-Subregion Based Probabilistic Approach Toward Pose-Invariant Face Recognition
Chapter 14:Morphable Models for Training a Component-Based Face Recognition System
Chapter 15: Model-Based Face Modeling and Tracking with Application to Video Conferencing
Chapter 16: 3D and MultiModal 3D & 2D Face Recognition
Chapter 17: Beyond One Still Image: Face Recognition from multiple Still Images or Video Sequence
Chapter 18: Subset Modeling of Face Localization Error, Occlusion and Expression
Chapter 19: Real-Time Robust Face and Facial Features Detection with Information-Based Maximum Discrimination
Chapter 20: Current Landscape of Thermal Infrared Face Recognition
Chapter 21: Multimodal Biometrics: Augmenting Face with Other Cues

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