Dynamic Vision: 

From Images to Face Recognition

Shaogang Gong, Stephen McKenna and Alexandra Psarrou
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Contents

PART I     BACKGROUND

1 About Face
The Visual Face, The Changing Face, Computing Faces, Biological Perspectives, The Approach

2 Perception and Representation
A Distal Object, Representation by 3D Reconstruction, Two-dimensional View-based Representation, Image Template-based Representation, The Correspondence Problem and Alignment, Biological Perspectives, Discussion

3 Learning Under Uncertainty
Statistical Learning, Learning as Function Approximation, Bayesian Inference and MAP Classification, Learning as Density Estimation, Unsupervised Learning without Density Estimation, Linear Classification and Regression, Non-linear Classification and Regression, Adaptation, Biological Perspectives, Discussion

PART II    FROM SENSORY TO MEANINGFUL PERCEPTION

4 Selective Attention: Where to Look
Pre-attentive Visual Cues from Motion, Learning Object-based Colour Cues, Perceptual Grouping for Selective Attention, Data Fusion for Perceptual Grouping, Temporal Matching and Tracking, Biological Perspectives, Discussion

5 A Face Model: What to Look For
Person-independent Face Models for Detection, Modelling the Face Class, Modelling a Near-face Class, Learning a Decision Boundary, Perceptual Search, Biological Perspectives, Discussion

6 Understanding Pose
Feature and Template-based Correspondence, The Face Space across Views: Pose Manifolds, Template Matching as Affine Transformation, Similarities to Prototypes across Views, Learning View-based Support Vector Machines, Biological Perspectives, Discussion

7 Prediction and Adaptation
Temporal Observations, Propagating First-order Markov Processes, Kalman Filters, Propagating Non-Gaussian Conditional Densities, Tracking Attended Regions, Adaptive Colour Models, Selective Adaptation, Tracking Faces, Pose Tracking, Biological Perspectives, Discussion

PART III    MODELS OF IDENTITY

8 Single-View Identification
Identification Tasks, Nearest-neighbour Template Matching, Representing Knowledge of Facial Appearance, Statistical Knowledge of Facial Appearance, Statistical Knowledge of Identity, Structural Knowledge: The Role of Correspondence, Biological Perspectives, Discussion

9 Multi-View Identification
View-based Models, The Role of Prior Knowledge, View Correspondence in Identification, Generalisation from a Single View, Generalisation from Multiple Views, Biological Perspectives, Discussion

10 Identifying Moving Faces
Biological Perspectives, Computational Theories of Temporal Identification, Identification using Holistic Temporal Trajectories, Identification by Continuous View Transformation, An Experimental System, Discussion

PART IV     PERCEPTION IN CONTEXT

11 Perceptual Integration
Sensory and Model-based Vision, Perceptual Fusion, Perceptual Inference, Vision as Co-operating Processes, Biological Perspectives, Discussion

12 Beyond Faces
Multi-modal Identification, Visually Mediated Interaction, Visual Surveillance and Monitoring, Immersive Virtual Reality, Visual Database Screening

PART V    APPENDICES

A Databases
Database Acquisition and Design, Acquisition of a Pose-labelled Database, Benchmarking, Commercial Databases, Public Domain Face Databases, Discussion

B Commercial Systems
System Characterisation, A View on the Industry, Discussion

C Mathematical Details
Principal Components Analysis, Linear Discriminant Analysis, Gaussian Mixture Estimation, Kalman Filters, Bayesian Belief Networks, Hidden Markov Models, Gabor Wavelets

Bibliography

Index

364 pp.



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