Advances in Face Image Analysis - Theory and Applications:
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Sharjah, U.A.E.
Bentham Science Publisher
[2016]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | III, 254 Seiten Illustrationen, Diagramme |
| ISBN: | 9781681081113 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804176134811680768 |
|---|---|
| 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
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191
192
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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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| spelling | Advances in Face Image Analysis - Theory and Applications edited by Fadi Dornaika, University of the Basque Country (UPV/EHU) Sharjah, U.A.E. Bentham Science Publisher [2016] III, 254 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Gesicht (DE-588)4020687-7 gnd rswk-swf Bildanalyse (DE-588)4145391-8 gnd rswk-swf Bildanalyse (DE-588)4145391-8 s Gesicht (DE-588)4020687-7 s DE-604 Dornaika, Fadi (DE-588)1103499963 edt Erscheint auch als Online-Ausgabe 978-1-68108-110-6 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf 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 Inhaltsverzeichnis |
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| 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 |
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