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Bibliographic Details
Other Authors:	Dornaika, Fadi (Editor)
Format:	Book
Language:	English
Published:	Sharjah, U.A.E. Bentham Science Publisher [2016]
Subjects:	Gesicht Bildanalyse
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028916537&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Physical Description:	III, 254 Seiten Illustrationen, Diagramme
ISBN:	9781681081113

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adam_text	CONTENTS FOREWORD ............................................................. i PREFACE ............................................................. ii LIST OF CONTRIBUTORS ............................................... iii CHAPTER I FACIAL EXPRESSION CLASSIFICATION BASED ON CONVOLUTIONAL NEURAL NETWORKS ......................................................................... 3 INTRODUCTION ................................................................. 3 Convolutional Neural Networks ............................................. 4 Facial Expression Analysis ................................................ 5 GRADIENT-BASED LEARNING FOR CNNS ............................................. 6 FEATURE GENERALIZATION ...................................................... 10 EXPERIMENTS ................................................................. 11 Datasets ................................................................. 11 CK-Regianini Dataset ................................................ 11 CK-Zheng Dataset ..................................................... 13 CMU-Pittsburgh dataset ............................................... 13 Experiments on CNN-based Facial Expression Classification ................ 13 Design ............................................................... 13 Results and Analysis ............................................... 14 Experiments on Feature Generalization .................................... 16 Design ............................................................. 16 Results and Analysis ................................................. 18 DISCUSSION .................................................................. 19 CONFLICT OF INTEREST ........................................................ 20 ACKNOWLEDGEMENTS .......................................................... 20 REFERENCES .................................................................. 20 CHAPTER 2 SPARSITY PRESERVING PROJECTION BASED CONSTRAINED GRAPH EMBEDDING AND ITS APPLICATION TO FACE RECOGNITION ......................................... 23 INTRODUCTION ................................................................ 24 RELATED WORK ................................................................ 25 Locality Preserving Projection ........................................... 25 Neighborhood Preserving Embedding ........................................ 27 Sparsity Preserving Projection ........................................... 28 Constrained Graph Embedding .......................................... 28 SPP BASED CONSTRAINED GRAPH EMBEDDING ....................................... 30 SPP-CGE ..................................................................... 30 Out-of-Sample Extension .............*.................................... 31 EXPERIMENTAL RESULTS ........................................................ 33 CONCLUSION .................................................................. 36 NOTES ....................................................................... 37 CONFLICT OF INTEREST ........................................................ 37 ACKNOWLEDGEMENTS ............................................................ 37 REFERENCES ...........................................................,...... 37 CHAPTER 3 FACE RECOGNITION USING EXPONENTIAL LOCAL DISCRIMINANT EMBEDDING ................................................................................... 39 INTRODUCTION ............................................................... 40 Contribution and Related Work ........................................... 42 REVIEW OF LOCAL DISCRIMINANT EMBEDDING (LDE) .............................. 44 Intrinsic Graph and Penalty Graph .................................. 44 Optimal Mapping ........................................................ 46 The Small Sample Size Problem ........................................... 47 EXPONENTIAL LDE ............................................................. 47 Matrix Exponential ...................................................... 48 Exponential LDE ........................................................ 48 THEORETICAL ANALYSIS OF ELDE ............................................... 50 Solving the SSS Problem ................................................ 50 Distance Diffusion Mapping ............................................. 50 PERFORMANCE EVALUATION ..................................................... 53 Face Databases ....................................................... 54 Recognition Accuracy ................................................... 54 Comparison between Regularized LDE and ELDE ............................ 59 CONCLUSION ................................................................. 60 NOTES ...................................................................... 61 CONFLICT OF INTEREST ....................................................... 61 ACKNOWLEDGMENTS ............................................................ 61 REFERENCES ................................................................. 62 CHAPTER 4 ADAPTIVE LOCALITY PRESERVING PROJECTIONS FOR FACE RECOGNITION .... 66 INTRODUCTION ............................................................... 67 LOCALITY PRESERVING PROJECTIONS ............................................ 68 ENHANCED AND PARAMETERLESS LPP ............................................. 71 PERFORMANCE EVALUATION ..................................................... 73 Face Databases ....................................................... 73 Experimental Results ................................................. 74 Performance Comparison for OLPP and SLPP ............................... 81 CONCLUSION ................................................................. 82 NOTES ...................................................................... 83 CONFLICT OF INTEREST ....................................................... 83 ACKNOWLEDGMENTS ............................................................ 83 REFERENCES ................................................................. 83 CHAPTER 5 FACE RECOGNITION USING 3D FACE RECTIFICATION ........................ 86 INTRODUCTION ............................................................... 86 PROPOSED METHOD ............................................................ 88 FACE DATABASE .............................................................. 89 PREPROCESSING .............................................................. 90 FACIAL FEATURE DETECTION .................................................... 91 POSE ESTIMATION ............................................................. 93 IRAD Contours .......................................................... 94 Ellipse Fitting And Roll Correction .................................... 95 Yaw Correction ......................................................... 96 Pitch Correction ....................................................... 97 Accuracy Of The Pose Estimation Method ............................... 98 ROTATION AND POST PROCESSING ............................................... 98 EXPERIMENTS ................................................................ 99 CONCLUSION .......................................................... 103 NOTES ............................................................... 104 CONFLICT OF INTEREST ................................................ 104 ACKNOWLEDGMENTS ..................................................... 104 REFERENCES .......................................................... 104 CHAPTER 6 3D FACE RECOGNITION .......................................... 109 INTRODUCTION ........................................................ 109 3D FACE ACQUISITION ................................................. Ill 3D FACE REPRESENTATION .............................................. 116 PREPROCESSING ....................................................... I 19 3D FACE ALIGNMENT ................................................... 122 FACE RECOGNITION .................................................... 124 CONCLUDING REMARKS .................................................. 127 CONFLICT OF INTEREST ................................................ 127 ACKNOWLEDGEMENTS .................................................... 128 REFERENCES .......................................................... 128 CHAPTER 7 MODEL-LESS 3D FACE POSE ESTIMATION ........................... 132 INTRODUCTION ........................................................ 132 STATE OF THE ART .................................................... 133 THE MACHINE LEARNING METHODOLOGY .................................... 134 Locality Preserving Projections ................................. 136 LPP Algorithm........................................ 136 Supervised Locality Preserving Projections ...................... 137 LABEL-SENSITIVE LOCALITY PRESERVING PROJECTION ...................... 138 Presetting: ..................................................... 138 Algorithm: ...................................................... 138 PROPOSED APPROACH: SPARSE GRAPH BASED LSLPP ......................... 139 EXPERIMENTAL RESULTS ................................................ 141 CONCLUSION .......................................................... 150 NOTES ............................................................... 150 CONFLICT OF INTEREST ................................................ 151 ACKNOWLEDGEMENTS .................................................... 151 REFERENCES .......................................................... 151 CHAPTER 8 EFFICIENT DEFORMABLE 3D FACE MODEL FITTING TO MONOCULAR IMAGES ... 154 INTRODUCTION ................................................... 155 LIGHTWEIGHT FACIAL FEATURE DETECTION ........................... 159 DEFORMABLE MODEL BACKPROJECTION ................................ 165 EXPERIMENTAL RESULTS AND DISCUSSION ............................ 167 CONCLUSION ..................................................... 173 APPENDIX A: MODIFICATIONS TO CANDIDE-3 ......................... 175 NOTES .......................................................... 175 CONFLICT OF INTEREST ........................................... 176 ACKNOWLEDGMENTS ................................................ 176 REFERENCES ..................................................... 176 CHAPTER 9 FACE DETECTION USING THE THEORY OF EVIDENCE ............. 181 INTRODUCTION ................................................... 182 STATE OF THE ART .................................... THEORY OF BELIEF FUNCTIONS Mass Sets ....................................... Modeling of Mass Functions ...................... Combination of Beliefs .......................... Management of Conflict .......................... Combination Rules for Dependent Sources ......... Decision with Transferable Belief Model ......... APPLICATION TO EVIDENTIAL FACE MODEL ................ Information Sources ............................. Mass Sets for VJ Face Detector .................. Color Mass Functions ............................ Color Fusion by Cautious Rule ................... Illustrative Example ........................ Global Fusion of Color and VJ Mass Sets by Conjunctive Rule Computation of Pignistic Probabilities .......... PROBABILISTIC FACE TRACKING ......................... Estimation of El lipse Center ................... Estimation of Size and Pose ..................... Visual Servoing ................................. PERFORMANCE ANALYSIS ................................ Qualitative Evaluation .......................... Quantitative Evaluation ......................... DISCUSSION ...................................... CONFLICT OF INTEREST ................................ ACKNOWLEDGEMENTS .................................... REFERENCES ........................................... CHAPTER 10 FUZZY DISCRIMINANT ANALYSIS: CONSIDERING THE FUZZINESS IN FACIAL AGE FEATURE EXTRACTION ............................................................. 217 INTRODUCTION ............................................................. 217 CHARACTERIZATION OF THE FUZZINESS IN FACIAL AGING .......................... 219 THE FUZZY DISCRIMINATIVE MANIFOLD ANALYSIS ................................. 221 Traditional Discriminative Manifold Methods ............................. 221 Fuzzy Discriminative Analysis for Age Estimation .................... 222 EXPERIMENTAL RESULTS ....................................................... 225 A Toy Example ........................................................... 225 Facial Age Estimation Results ........................................... 227 Databases ......................................................... 227 Experimental Setting ................................................ 227 Experiments on the FGNET Database ................................... 228 Experiments on the MORPH Database ................................... 229 CONCLUSION ................................................................. 231 CONFLICT OF INTEREST ....................................................... 231 ACKNOWLEDGEMENTS ........................................................... 232 REFERENCES ................................................................. 232 CHAPTER 11 FACIAL IMAGE-BASED AGE ESTIMATION ................................... 234 INTRODUCTION .............................................................. 234 AGE ESTIMATION ALGORITHMS ................................................. 235 Input Images Preprocessing .............................................. 236 183 185 185 187 189 190 190 191 192 193 194 195 197 198 199 201 202 205 207 207 208 208 210 212 213 213 213 Feature Extraction ...................................................... 236 Distance Metric Adjustments ............................................. 237 Dimensionality Reduction ................................................ 238 Age Determination ....................................................... 238 AGE ESTIMATION FRAMEWORK AND EXPERIMENTS PEREORMED ......................... 239 EXPERIMENTAL SETTING ....................................................... 240 Datasets ................................................................ 240 Performance Scores .................................................. 242 RESULTS .................................................................... 242 CONCLUSION ................................................................. 246 CONFLICT OF INTEREST ....................................................... 247 ACKNOWLEDGEMENTS ........................................................... 247 REFERENCES ................................................................. 247 SUBJECT INDEX 251
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physical	III, 254 Seiten Illustrationen, Diagramme
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spellingShingle	Advances in Face Image Analysis - Theory and Applications Gesicht (DE-588)4020687-7 gnd Bildanalyse (DE-588)4145391-8 gnd
subject_GND	(DE-588)4020687-7 (DE-588)4145391-8
title	Advances in Face Image Analysis - Theory and Applications
title_auth	Advances in Face Image Analysis - Theory and Applications
title_exact_search	Advances in Face Image Analysis - Theory and Applications
title_full	Advances in Face Image Analysis - Theory and Applications edited by Fadi Dornaika, University of the Basque Country (UPV/EHU)
title_fullStr	Advances in Face Image Analysis - Theory and Applications edited by Fadi Dornaika, University of the Basque Country (UPV/EHU)
title_full_unstemmed	Advances in Face Image Analysis - Theory and Applications edited by Fadi Dornaika, University of the Basque Country (UPV/EHU)
title_short	Advances in Face Image Analysis - Theory and Applications
title_sort	advances in face image analysis theory and applications
topic	Gesicht (DE-588)4020687-7 gnd Bildanalyse (DE-588)4145391-8 gnd
topic_facet	Gesicht Bildanalyse
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028916537&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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