Human emotion recognition from face images

Preface......Page 7
Acknowledgements......Page 11
Contents......Page 12
About the Authors......Page 17
1 Introduction......Page 18
  1.1.1 Types of Emotions......Page 20
 1.2 Database of Facial Expression......Page 24
 1.3 Survey Work......Page 29
 1.4 Sum-up Discussion......Page 35
 References......Page 36
 2.1 Introduction......Page 38
 2.2 Block Diagram of Proposed Emotion Recognition System......Page 39
  2.2.1 Landmark Detection Using AAM......Page 40
  2.2.2 Formation of Grid......Page 41
  2.3.1 Distance Signature......Page 44
  2.3.2 Stability Index......Page 45
  2.3.3 Statistical Measures of Distance Signature......Page 47
 2.5 Training of MLP......Page 49
  2.5.1 Classification......Page 51
  2.6.1 Experimental Result on CK+ Dataset......Page 52
  2.6.2 Experimental Result on JAFFE Dataset......Page 54
  2.6.3 Experimental Result on MMI Dataset......Page 55
  2.6.4 Experimental Result on MUG Dataset......Page 57
  2.6.5 Comparative Analyses......Page 58
 References......Page 61
 3.1 Introduction......Page 63
 3.2 Proposed Framework of Shape Signature's Emotion Detection......Page 64
  3.2.2 Triangle Formation......Page 65
  3.3.1 Shape Signature......Page 67
  3.3.3 Range, Moment, Skewness, Kurtosis, and Entropy......Page 69
 3.4 Classification Using MLP and NARX......Page 70
  3.4.1 NARX Training......Page 72
 3.5 Experiment and Result......Page 73
  3.5.1 Experiment on Cohn-Kanade (CK+)......Page 75
  3.5.2 Experiment on JAFFE Database......Page 77
  3.5.3 Experiment on MMI Database......Page 80
  3.5.4 Experiment on MUG Database......Page 83
  3.5.5 Comparison of Result with Different State of the Art......Page 85
 References......Page 88
 4.1 Introduction......Page 90
  4.2.1 Landmark Detection......Page 91
  4.2.2 Texture Region......Page 92
  4.2.3 Local Binary Pattern......Page 94
 4.3 Feature Extraction......Page 95
  4.3.1 Stability Index of Texture Signature......Page 96
  4.3.2 Statistical Measures of Texture Signature......Page 97
  4.4.1 Experimental Result on the CK+......Page 98
  4.4.2 Experimental Result on the JAFFE......Page 100
  4.4.3 Experiment on MMI Database......Page 101
  4.4.4 Experiment on MUG Database......Page 102
  4.4.5 Performance Measure with State of the Art......Page 103
 4.5 Discussion......Page 105
 References......Page 106
 5.1 Introduction......Page 107
 5.2 Schematic Diagram of Facial Expression Recognition......Page 108
  5.2.3 Formation of Distance-Shape (D-S) Signature......Page 110
 5.3 Feature Classification by MLP Training......Page 111
 5.4 Experiment on Four Benchmark Databases and Result Analysis......Page 113
  5.4.1 Experiment and Result on CK+ Database......Page 114
  5.4.2 Experiment and Result on JAFFE Dataset......Page 116
  5.4.3 Experiment and Result on MMI Database......Page 118
  5.4.4 Experiment and Result on MUG Dataset......Page 121
  5.4.5 Experiment and Result of D-S Signature on CK+, JAFFE, MMI, and MUG Databases......Page 123
  5.4.6 Performance Comparison of FRR, FAR, and ERR of Distance, Shape, and D-S Signatures......Page 127
  5.4.7 Comparison with Different State of the Art......Page 133
 References......Page 136
 6.1 Introduction......Page 138
 6.2 Proposed System of Emotion Recognition......Page 139
  6.2.1 Facial Grid Formation Using Detected Landmark......Page 140
  6.2.3 Feature Extraction......Page 142
 6.3 Feature Selection and Classification......Page 143
  6.3.2 Radial Basis Function Training Mechanism......Page 146
  6.3.3 Training Using Nonlinear Auto Regressive with eXogenous Input......Page 147
  6.4.1 Evaluated Result on the CK+ Dataset......Page 148
  6.4.2 Result Evaluation on the JAFFE Dataset......Page 158
  6.4.3 Experiment on MMI Database......Page 166
  6.4.4 Experimental Result on MUG Dataset......Page 175
 6.5 Discussion......Page 183
  6.5.1 Performance Measure with State of the Art......Page 186
 6.6 Sum-up Discussion......Page 187
 References......Page 188
 7.1 Introduction......Page 190
 7.2 Overview of Proposed Facial Expression Recognition......Page 191
 7.3 Formation of Grid and Triangle......Page 192
  7.3.2 Shape Signature and Texture Signature......Page 193
  7.3.4 Statistical Analysis of Shape and Texture Signature Features......Page 194
  7.4.1 The Training Procedure of MLP......Page 195
  7.4.2 Training Procedure of Deep Belief Network......Page 196
  7.5.1 Experimental Result on CK+ Dataset......Page 197
  7.5.4 Experimental Result on JAFFE Dataset......Page 206
  7.5.5 Experiment on MMI Database......Page 216
  7.5.6 Experimental Result on MUG Dataset......Page 224
  7.5.7 Experiment on Wild Database......Page 233
 7.6 Performance Analysis of FAR, FRR, and ERR on CK+, JAFFE, …......Page 239
 7.8 Conclusion......Page 244
 References......Page 246
 8.1 Introduction......Page 248
 8.2 Overview of the Proposed System......Page 249
  8.3.1 Grid Formation......Page 250
  8.4.2 Range, Moment, Skewness, Kurtosis, and Entropy from Distance-Shape-Texture Signature Trio......Page 251
  8.6.1 Multilayer Perceptron......Page 252
  8.6.2 Training Using Nonlinear Auto Regressive with eXogenous Input......Page 253
 8.7 Experiment and Result......Page 254
  8.7.1 Experiment on CK+ Database......Page 255
  8.7.2 Experimental Result on JAFFE Database......Page 259
  8.7.3 Experiment on MMI Database......Page 263
  8.7.4 Experiment on MUG Database......Page 267
  8.7.5 Compare Analysis with Three Artificial Networks and State of the Arts......Page 270
 References......Page 273
Index......Page 275