Face Processing: Advanced Modeling and Methods

Face Processing: Advanced Modeling and Methods

1st Edition - December 28, 2005

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  • Editors: Wenyi Zhao, Rama Chellappa
  • eBook ISBN: 9780080488844

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Description

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. Face Processing: Advanced Modeling and Methods begins with a comprehensive introductory chapter for those who are new to the field. A compendium of articles follows that is divided into three sections. The first covers basic aspects of face processing from human to computer. The second deals with face modeling from computational and physiological points of view. The third tackles the advanced methods, which include illumination, pose, expression, and more. Editors Zhao and Chellappa have compiled a concise and necessary text for industrial research scientists, students, and professionals working in the area of image and signal processing.

Key Features

  • Contributions from over 35 leading experts in face detection, recognition and image processing
  • Over 150 informative images with 16 images in FULL COLOR illustrate and offer insight into the most up-to-date advanced face processing methods and techniques
  • Extensive detail makes this a need-to-own book for all involved with image and signal processing

Readership

Researchers, students and professors in signal/image processing, computer vision, pattern recognition, machine learning, computer graphics, psychology, and neuroscience

Table of Contents

  • Dedication

    CONTRIBUTORS

    PREFACE

    PART I: THE BASICS

    Chapter 1: A GUIDED TOUR OF FACE PROCESSING

    1.1 INTRODUCTION TO FACE PROCESSING

    1.2 FACE PERCEPTION: THE PSYCHOPHYSICS/NEUROSCIENCE ASPECT

    1.3 FACE DETECTION AND FEATURE EXTRACTION

    1.4 METHODS FOR FACE RECOGNITION

    1.5 ADVANCED TOPICS IN FACE RECOGNITION

    ACKNOWLEDGMENTS

    Chapter 2: EIGENFACES AND BEYOND

    2.1 INTRODUCTION

    2.2 ORIGINAL CONTEXT AND MOTIVATIONS OF EIGENFACES

    2.3 EIGENFACES

    2.4 IMPROVEMENTS TO AND EXTENSIONS OF EIGENFACES

    2.5 SUMMARY

    ACKNOWLEDGMENTS

    Chapter 3: INTRODUCTION TO THE STATISTICAL EVALUATION OF FACE-RECOGNITION ALGORITHMS

    3.1 INTRODUCTION

    3.2 FACE-IDENTIFICATION DATA, ALGORITHMS, AND PERFORMANCE MEASURES

    3.3 A BERNOULLI MODEL FOR ALGORITHM TESTING

    3.4 NONPARAMETRIC RESAMPLING METHODS

    3.5 EXPANDING THE LDA VERSUS PCA COMPARISON

    3.6 ADVANCED MODELING

    3.7 CONCLUSION

    Appendix A NOTATIONAL SUMMARY

    Appendix B PARTICULARS FOR THE ELASTIC BUNCH GRAPH ALGORITHM

    ACKNOWLEDGMENTS

    PART II: FACE MODELING COMPUTATIONAL ASPECTS

    Chapter 4: 3D MORPHABLE FACE MODEL, A UNIFIED APPROACH FOR ANALYSIS AND SYNTHESIS OF IMAGES

    4.1 INTRODUCTION

    4.2 PARAMETERS OF VARIATION IN IMAGES OF HUMAN FACES

    4.3 TWO- OR THREE-DIMENSIONAL IMAGE MODELS

    4.4 IMAGE ANALYSIS BY MODEL FITTING

    4.5 MORPHABLE FACE MODEL

    4.6 COMPARISON OF FITTING ALGORITHM

    4.7 RESULTS

    4.8 CONCLUSION

    Chapter 5: EXPRESSION-INVARIANT THREE-DIMENSIONAL FACE RECOGNITION

    5.1 INTRODUCTION

    5.2 ISOMETRIC MODEL OF FACIAL EXPRESSIONS

    5.3 EXPRESSION-INVARIANT REPRESENTATION

    5.4 THE 3DFACE SYSTEM

    5.5 RESULTS

    5.6 CONCLUSIONS

    ACKNOWLEDGMENTS

    Chapter 6: 3D FACE MODELING FROM MONOCULAR VIDEO SEQUENCES

    6.1 INTRODUCTION

    6.2 SFM-BASED 3D FACE MODELING

    6.3 CONTOUR-BASED 3D FACE MODELING

    6.4 CONCLUSIONS

    Chapter 7: FACE MODELING BY INFORMATION MAXIMIZATION

    7.1 INTRODUCTION

    7.2 INDEPENDENT-COMPONENT ANALYSIS

    7.3 IMAGE DATA

    7.4 ARCHITECTURE I: STATISTICALLY INDEPENDENT BASIS IMAGES

    7.5 ARCHITECTURE II: A FACTORIAL FACE CODE

    7.6 EXAMINATION OF THE ICA REPRESENTATIONS

    7.7 LOCAL BASIS IMAGES VERSUS FACTORIAL CODES

    7.8 DISCUSSION

    7.9 FACE MODELING AND INFORMATION MAXIMIZATION: A COMPUTATIONAL NEUROSCIENCE PERSPECTIVE

    ACKNOWLEDGMENTS

    Chapter 8: FACE RECOGNITION BY HUMANS

    8.1 INTRODUCTION

    8.2 WHAT ARE THE LIMITS OF HUMAN FACE RECOGNITION SKILLS?

    8.3 WHAT CUES DO HUMANS USE FOR FACE-RECOGNITION?

    8.4 WHAT IS THE TIMELINE OF DEVELOPMENT OF HUMAN FACE RECOGNITION SKILLS?

    8.5 WHAT ARE SOME BIOLOGICALLY PLAUSIBLE STRATEGIES FOR FACE RECOGNITION?

    8.6 CONCLUSION

    Chapter 9: PREDICTING HUMAN PERFORMANCE FOR FACE RECOGNITION

    9.1 INTRODUCTION

    9.2 FACE-BASED FACTORS AND THE FACE-SPACE MODEL

    9.3 VIEWING CONSTRAINTS

    9.4 MOVING FACES

    9.5 MOTION AND FAMILIARITY

    9.6 FAMILIARITY AND EXPERIENCE

    ACKNOWLEDGMENTS

    Chapter 10: SPATIAL DISTRIBUTION OF FACE AND OBJECT REPRESENTATIONS IN THE HUMAN BRAIN

    10.1 THE VENTRAL OBJECT-VISION PATHWAY

    10.2 LOCALLY DISTRIBUTED REPRESENTATIONS OF FACES AND OBJECTS IN VENTRAL TEMPORAL CORTEX

    10.3 EXTENDED DISTRIBUTION OF FACE AND OBJECT REPRESENTATIONS

    10.4 SPATIALLY DISTRIBUTED FACE AND OBJECT REPRESENTATIONS

    PART III: ADVANCED METHODS

    Chapter 11: ON THE EFFECT OF ILLUMINATION AND FACE RECOGNITION

    11.1 INTRODUCTION

    11.2 NON-EXISTENCE OF ILLUMINATION INVARIANTS

    11.3 THEORY AND FOUNDATIONAL RESULTS

    11.4 MENAGERIE

    11.5 EXPERIMENTS AND RESULTS

    11.6 CONCLUSION

    ACKNOWLEDGMENT

    Chapter 12: MODELING ILLUMINATION VARIATION WITH SPHERICAL HARMONICS

    12.1 INTRODUCTION

    12.2 BACKGROUND AND PREVIOUS WORK

    12.3 ANALYZING LAMBERTIAN REFLECTION USING SPHERICAL HARMONICS

    12.4 APPLICATIONS OF LAMBERTIAN 9-TERM SPHERICAL-HARMONIC MODEL

    12.5 SPECULARITIES: CONVOLUTION FORMULA FOR GENERAL MATERIALS

    12.6 RELAXING AND BROADENING THE ASSUMPTIONS: RECENT WORK

    12.7 CONCLUSION

    ACKNOWLEDGMENTS

    Chapter 13: A MULTISUBREGION-BASED PROBABILISTIC APPROACH TOWARD POSE-INVARIANT FACE RECOGNITION

    13.1 INTRODUCTION

    13.2 MODELING CHANGE OF LOCAL APPEARANCE ACROSS POSES

    13.3 RECOGNITION

    13.4 RECOGNITION EXPERIMENTS

    13.5 CONCLUSION

    Chapter 14: MORPHABLE MODELS FOR TRAINING A COMPONENT-BASED FACE-RECOGNITION SYSTEM

    14.1 INTRODUCTION

    14.2 MORPHABLE MODELS

    14.3 FACE DETECTION AND RECOGNITION

    14.4 EXPERIMENTAL RESULTS

    14.5 LEARNING COMPONENTS FOR FACE RECOGNITION

    14.6 SUMMARY AND OUTLOOK

    Chapter 15: MODEL-BASED FACE MODELING AND TRACKING WITH APPLICATION TO VIDEOCONFERENCING

    15.1 INTRODUCTION

    15.2 STATE OF THE ART

    15.3 FACIAL GEOMETRY REPRESENTATION

    15.4 OVERVIEW OF THE 3D FACE-MODELING SYSTEM

    15.5 A TOUR OF THE SYSTEM ILLUSTRATED WITH A REAL VIDEO SEQUENCE

    15.6 MORE FACE-MODELING EXPERIMENTS

    15.7 STEREO 3D HEAD-POSE TRACKING

    15.8 APPLICATION TO EYE-GAZE CORRECTION

    15.9 CONCLUSIONS

    ACKNOWLEDGMENT

    Chapter 16: A SURVEY OF 3D AND MULTIMODAL 3D+2D FACE RECOGNITION

    16.1 INTRODUCTION

    16.2 SURVEY OF 3D AND MULTIMODAL 2D+3D FACE RECOGNITION

    16.3 EXAMPLE 3D AND MULTIMODAL 3D+2D FACE RECOGNITION

    16.4 CHALLENGES TO IMPROVED 3D FACE RECOGNITION

    ACKNOWLEDGMENTS

    Chapter 17: BEYOND ONE STILL IMAGE: FACE RECOGNITION FROM MULTIPLE STILL IMAGES OR A VIDEO SEQUENCE

    17.1 INTRODUCTION

    17.2 BASICS OF FACE RECOGNITION

    17.3 PROPERTIES

    17.4 REVIEW

    17.5 FUTURE

    17.6 CONCLUSIONS

    Chapter 18: SUBSET MODELING OF FACE LOCALIZATION ERROR, OCCLUSION, AND EXPRESSION

    18.1 INTRODUCTION

    18.2 MODELING THE LOCALIZATION ERROR

    18.3 MODELING OCCLUSIONS AND EXPRESSION CHANGES

    18.4 EXPERIMENTAL RESULTS

    18.5 DISCUSSION AND FUTURE WORK

    18.6 CONCLUSIONS

    Acknowledgments

    Chapter 19: NEAR REAL-TIME ROBUST FACE AND FACIAL-FEATURE DETECTION WITH INFORMATION-BASED MAXIMUM DISCRIMINATION

    19.1 INTRODUCTION

    19.2 INFORMATION-BASED MAXIMUM DISCRIMINATION

    19.3 IBMD FACE AND FACIAL-FEATURE DETECTION

    19.4 EXPERIMENTS AND RESULTS

    19.5 CONCLUSIONS AND FUTURE WORK

    Chapter 20: CURRENT LANDSCAPE OF THERMAL INFRARED FACE RECOGNITION

    20.1 INTRODUCTION

    20.2 PHENOMENOLOGY

    20.3 SAME-SESSION RECOGNITION

    20.4 TIME-LAPSE RECOGNITION

    20.5 OUTDOOR RECOGNITION

    20.6 RECOGNITION IN THE DARK WITH THERMAL INFRARED

    20.7 CONCLUSION

    ACKNOWLEDGMENT

    Chapter 21: MULTIMODAL BIOMETRICS: AUGMENTING FACE WITH OTHER CUES

    21.1 INTRODUCTION

    21.2 DESIGN OF A MULTIMODAL BIOMETRIC SYSTEM

    21.3 EXAMPLES OF MULTIMODAL BIOMETRIC SYSTEMS

    21.4 CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS

    INDEX

Product details

  • No. of pages: 768
  • Language: English
  • Copyright: © Academic Press 2005
  • Published: December 28, 2005
  • Imprint: Academic Press
  • eBook ISBN: 9780080488844

About the Editors

Wenyi Zhao

Affiliations and Expertise

Editor Sarnoff Corporation, Princeton, NJ, USA

Rama Chellappa

Affiliations and Expertise

University of Maryland, College Park, MD, USA

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