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1 Introduction ............. .................. .......... 1 1.1 Tasks and Protocols ................... ............... 4 1.2 Biometrics System Design . .................. ......... . 7 1.3 History .......... . .................... ............ 8 1.4 Road Map ............... ........................... 13 2 The Human Face ............. ......................... 15 2.1 Cognitive Neurosciences ........... . . . . ............... . 16 2.2 Psychophysics..................................... 19 2.3 The Social Face .................. ....................... 26 2.4 Aesthetics and Arts.............. ....... ............... 30 3 Modeling and Prediction ................ ................ 35 3.1 Bayesian Inference ............. .... .................. . 37 3.2 Connectionism ................... ........................ 40 3.3 Regularization ...................................... 43 3.4 Structural Risk Minimization .................. ......... . 44 3.5 Transduction ....................................... 48 3.6 Generative and Discriminative Methods ................. ... 50 4 Data Collection ........................................... 53 4.1 Sensing ............................................. 53 4.2 Standards .............. ............................ 56 4.3 Data Compression ................................ .. 58 5 Face Representation .................. ........... .. . 65 5.1 The Face Space ............ ........................ 65 5.2 Scale Space .............. ........ . . ................ 68 5.3 Invariance .............. ........................... . 72 5.4 Subspace Methods.................... . .............. . 74 5.5 Feature Selection .................. . .. . ............. .. 80 5.6 Caricatures ................ ......................... 85 5.7 Kernel Methods ................... ......... .. ....... 91 5.8 Color .................................... .............. 94 6 Face Recognition ............ ......................... 97 6.1 Metrics .............. ............................ 97 6.2 Verification and Identification .................. ......... . 99 6.3 Open Set Recognition ................... .................. 102 6.4 Watch List and Surveillance . .................. ........ 107 6.5 Recognition-by-Parts ......... . . . . . . .................. 110 6.6 Face Selection ...................................... 115 6.7 Categorization ............. ........................... 116 6.8 Morphometrics ..................................... 118 7 Face in a Crowd ................... .................. 121 7.1 Face Detection .................. ................... ... 121 7.2 Eye Detection ............... .................... 125 7.3 Uncertainty ........................................... 128 7.4 Active Learning and Evidence Accumulation ................. 130 7.5 Video Break Detection and Key Frame Extraction ............ 135 7.6 Pose Detection and Manifolds ......... . . ......... ..... 137 7.7 Tracking and Recognition from Video ....................... 143 7.8 Spatio-Temporal Subspace Analysis Using 3D ICA............ 150 8 3D ............. . . ........................ .............. 155 8.1 Sensing ................... ......... .................. 156 8.2 Analysis by Synthesis . . . . . . ................. ...... . . 159 8.3 Animation ......................... ...................... 160 8.4 Modeling and Recognition . . . . . ................. .... . . 162 9 Data Fusion ............. ................ .......... 169 9.1 Multiple Cues ............. ........................ 169 9.2 Multiple Engines ............. ................... 171 9.3 Voting Schemes .................................... 174 9.4 Multiple Samples ................................... 177 9.5 Multimodal Sensory Integration .................. . . . . . . ... 179 9.6 Soft Biometrics................. .. .................. 181 9.7 Boosting and Strangeness ........... ....... ...... . . . . . . . 182 10 Denial and Deception..................... ............... 191 10.1 Human Biases...................................... 192 10.2 Camouflage ....................................... 193 10.3 Aliveness Detection .......... . . . . ................... . 195 10.4 Hallucinations ................... ........................ 196 10.5 Asymmetric Faces ................ ..................... 197 10.6 Adaptive and Robust Correlation Filters .................... 199 10.7 Associative, Distributed and Holographic Memories ........... 208 11 Augmented Cognition ....................... ........... 213 11.1 Paralanguage ............... ......................... 214 11.2 Face Expressions ......... ....................... 215 11.3 W5+ .......... . .................. ............ 218 12 Performance Evaluation .................... ................ 223 12.1 Figures of Merit .................................... 223 12.2 Score Normalization ................... ................... 229 12.3 Decision Thresholds .......... . . . . .................. . 231 12.4 Comparative Assessment .......... . . . . ............... 233 12.5 Data Bases ..................... ........................... 236 12.6 Virtual Samples.............. ......................... 240 13 Error Analysis ................... . ................... 243 13.1 Confidence Intervals .......... . . . . .................. . 244 13.2 Prevalence and Fallacies .......... . . . . .. ............. . 248 13.3 Pattern Specific Error Inhomogeneities .................. ... 251 13.4 Large Scale Biometric Evaluations ......................... 255 14 Security and Privacy ................... .................... 261 14.1 Diversity and Uniqueness .................................. 264 14.2 Regeneration of Face Images from Biometric Templates ....... 266 14.3 Cryptography ........................................... 267 14.4 Steganography and Digital Watermarking .................. 268 14.5 Anonymity ......................... ..................... 270 14.6 Photofits ......................... ....................... 273