Cover; Craniofacial Identification; Title; Copyright; Contents; Contributors; Part I: Identification of the Living; Chapter 1: Familiar face recognition; 1.1 Introduction; 1.2 Familiar versus unfamiliar face recognition; 1.3 Individual differences in face recognition; 1.4 Stages in person recognition; 1.5 Contextual factors in person recognition; 1.6 Conclusions; References; Notes; Chapter 2: Unfamiliar face recognition; Chapter 3: EFIT-V: Evolutionary algorithms and computer composites; 3.1 Introduction; 3.1.1 Historical background to holistic composite systems
3.2 Mathematical model of facial appearance3.2.1 Training -- the generation of the facial appearance model; 3.2.2 Decomposition of a face into appearance parameters; 3.2.3 Synthesis of a face from its appearance parameters; 3.2.4 Summary of appearance model properties; 3.2.5 Significance of appearance model representation; 3.2.6 Stochastic search algorithm; 3.3 Systematic operations in the EFIT-V system; 3.3.1 Locking facial features; 3.3.2 Feature clone tool; 3.3.3 Blend tool; 3.3.4 Facial attribute manipulation; 3.3.5 Local feature manipulation; 3.3.6 Applying fine details to a composite
3.4 The use of EFIT-V -- operational procedure3.4.1 Use of EFIT-V and future development; Chapter 4: Facial recall and computer composites; 4.1 Introduction; 4.2 Introduction to face systems and cognitive processes; 4.3 Facial recall; 4.4 Computerised feature systems; 4.5 Composite system performance; 4.6 What could be going wrong?; 4.7 Improving computer composites; 4.7.1 Morphing; 4.7.2 Interviewing; 4.7.3 Caricature; 4.7.4 System; 4.7.5 System: EFIT-V; 4.7.6 System: EvoFIT; 4.8 The future; 4.9 Concluding comments; Answers; Acknowledgement; References; Chapter 5: Facial ageing
5.1 Introduction5.1.1 Desirable features of an ageing system; 5.2 Non-statistical methods; 5.3 Facial composites; 5.3.1 A face description model; 5.3.2 Building a prototype; 5.3.3 The efficacy of prototype face images; 5.4 Statistical representation of faces; 5.5 Ageing using principal components analysis; 5.6 Trajectories; 5.7 3D; 5.8 Partial least squares; 5.9 Fine detail analysis; 5.10 Conclusion; References; Chapter 6: Age progression and regression; 6.1 Introduction; 6.2 Age progression; 6.3 Juvenile age progression; 6.4 Ageing adults; 6.5 Age regression; References
Chapter 7 Computer-assisted age progression7.1 Introduction; 7.2 Background; 7.3 Computer-assisted method for ageing faces; 7.3.1 Stages of facial development -- piece-wise axes; 7.4 Extension of the ageing model to reflect genetic bias; 7.5 Applying fine details to an aged face; 7.5.1 Extracting wrinkle-maps from sample images; 7.5.2 Applying details to a target face; 7.6 Examples of age-progressed faces; 7.7 Summary and conclusions; References; Chapter 8: Facial recognition from identification parades; 8.1 Introduction; 8.2 The eyewitness paradigm; 8.3 Line-up formats
Summary
Draws together a wide range of elements relating to craniofacial analysis and identification, examining the latest advances in the field
