Face Processing: Advanced Modeling and Methods - 1st Edition - ISBN: 9780120884520, 9780080488844

Face Processing: Advanced Modeling and Methods

1st Edition

Editors: Wenyi Zhao Rama Chellappa
Hardcover ISBN: 9780120884520
eBook ISBN: 9780080488844
Imprint: Academic Press
Published Date: 28th December 2005
Page Count: 768
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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.

This book 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

Details

No. of pages:
768
Language:
English
Copyright:
© Academic Press 2005
Published:
Imprint:
Academic Press
eBook ISBN:
9780080488844
Hardcover ISBN:
9780120884520

About the Editor

Wenyi Zhao

Affiliations and Expertise

Editor Sarnoff Corporation, Princeton, NJ, USA

Rama Chellappa

Affiliations and Expertise

University of Maryland, College Park, MD, USA