目录 Chapter 1 Introduction 1.1 Why Faces with Multi-Characteristics 1.2 Fa Authentication Using Permanent Spe Features 1.3 Fa Beauty Analysis Using Permanent Common Features 1.4 Fa Diagnosis by Disease Changed Features 1.5 Expression Recognition by Stimulus Changed Features 1.6 Outline of This Book References PART I FACIAL AUTHENTICATION Chapter 2 Fa Authentication Overview 2.1 Introduction 2.1.1 History of Automated Fa Recognition Research 2.1.2 Classification of Fa Recognition Scenarios 2.1.3 Challenges in Automated Fa Recognition 2.2 Permanent Unique Features for Fa Recognition 2.2.1 Geometric Features 2.2.2 Appearance Features 2.3 Fa Recognition: Systems and Applications 2.3.1 Major Modules in Automated Fa Recognition Systems 2.3.2 Application Modes 2.4 Chapters Overview 2.5 Summary References Chapter 3 Evolutionary Discriminant Feature Based Fa Recognition 3.1 Introduction 3.2 Evolutionary Discriminant Feature Extraction 3.2.1 Data Preprocessing: Centralization and Whitening 3.2.2 Calculating the Constrained Search Space 3.2.3 Searching: An Evolutionary Approach 3.2.4 Bagging EDFE 3.3 Fa Recognition Experiments 3.3.1 Databases and Parameter Settings 3.3.2 Investigation on Different Subspaces 3.3.3 Investigation on Dimensionality of Feature Subspaces 3.3.4 Performance Comparison 3.3.5 Discussion 3.4 Summary References Chapter 4 Fa Identification by Gabor Feature Based Robust Representation 4.1 Introduction 4.2 Related Work 4.2.1 Sparse Representation Based Classification(SRC) 4.2.2 Collaborative Representation Based Classification(CRC) 4.2.3 Gabor Features 4.3 Gabor-Feature Based Robust Representation and Classification 4.3.1 Gabor-Feature Based Robust Representation 4.3.2 Discussion on Occlusion Dictionary 4.3.3 Gabor Occlusion Dictionary(GOD)Computing 4.3.4 GRR Based Classification(GRRC) 4.3.5 Time Complexity 4.4 Experimental Results 4.4.1 Gabor Features and Regularization of GOD Computing 4.4.2 Face Recognition with Little Deformation 4.4.3 Face Recognition with Pose and Expression Variations 4.4.4 Recognition Against Occlusion 4.5 Discussion of Regularization on Coding Coefficients 4.6 Summary References Chapter 5 Three Dimension Enhanced Fa Identification 5.1 Introduction 5.2 Joint Face Alignment and 3D Face Reconstruction 5.2.1 Overview 5.2.2 Training Data Preparation 5.2.3 Learning Landmark Regressors 5.2.4 Estimating 3D-to-2D Mapping and Landmark Visibility 5.3 Application to Face Recognition 5.4 Experiments 5.4.1 Protocols 5.4.2 3D Face Reconstruction Accuracy 5.4.3 Face Alignment Accuracy 5.4.4 Face Recognition Accuracy 5.4.5 Computational Efficiency 5.5 Summary References PART II FACIAL BEAUTY ANALYSIS PART III FACIAL DIAGNOSIS PART IV FACIAL EXPRESSION RECOGNITION Index
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