Kumar Datta, Asit
Face Detection And Recognition Theory And Practice - 1A. ed - ESTADOS UNIDOS CRC PRESS 2016 - 325 23.5
Contents
. -- List Of Figures
. -- List Of Tables
. -- Preface
. -- Acknowledgment
. -- Introduction
. -- Introduction
. -- Biometric Identity Authentication Techniques
. -- Face As Biometric Identity
. -- Automated Face Recognition System
. -- Process Flow In Face Recognition System
. -- Problems Of Face Detection And Recognition
. -- Liveness Detection For Face Recognition
. -- Tests And Metrics
. -- Cognitive Psychology In Face Recognition
. -- Face Detection And Recognition Techniques
. -- Introduction To Face Detection
. -- Feature-Based Approaches For Face Detection
. -- Low-Level Analysis
. -- Edges
. -- Gray-Level Analysis
. -- Color Information In Face Detection
. -- Motion-Based Analysis
. -- Active Shape Model
. -- Feature Analysis
. -- Image-Based Approaches For Face Detection
. -- Statistical Approaches
. -- Face Recognition Methods
. -- Geometric Feature-Based Method
. -- Subspace-Based Face Recognition
. -- Neural Network-Based Face Recognition
. -- Correlation-Based Method
. -- Matching Pursuit-Based Methods
. -- Support Vector Machine Approach
. -- Selected Works On Face Classifiers
. -- Face Reconstruction Techniques
. -- Three-Dimensional Face Recognition
. -- Feature Extraction
. -- Global Feature Extraction
. -- Three-Dimensional Morphable Model
. -- Subspace Based Face Recognition
. -- Introduction
. -- Principal Component Analysis
. -- Two-Dimensional Principal Component Analysis
. -- Kernel Principal Component Analysis
. -- Fisher Linear Discriminant Analysis
. -- Fisher Linear Discriminant Analysis For Two-Class Case
. -- Independent Component Analysis
. -- Face Detection By Bayesian Approach
. -- Introduction
. -- Bayes Decision Rule For Classification
. -- Gaussian Distribution
. -- Bayes Theorem
. -- Bayesian Decision Boundaries And Discriminant Function
. -- Density Estimation Using Eigenspace Decomposition
. -- Bayesian Discriminant Feature Method
. -- Modelling Of Face And Non-Face Pattern
. -- Bayes Classification Using Bdf
. -- Experiments And Results
. -- Face Detection In Color And Infrared Images
. -- Introduction
. -- Face Detection In Color Images
. -- Color Spaces
. -- Rgb Model
. -- Hsi Color Model
. -- Ycbcr Color Space
. -- Face Detection From Skin Regions
. -- Skin Modelling
. -- Skin Color Modelling Explicitly From Rgb Space
. -- Skin Color Modelling Explicitly From Ycbcr Space
. -- Probabilistic Skin Detection
. -- Face Detection By Localizing Facial Features
. -- Eyemap
. -- Mouthmap
. -- Face Detection In Infrared Images
. -- Multivariate Histogram-Based Image Segmentation
. -- Method For Finding Major Clusters From a Multivariate Histogram
. -- Experiments And Results On The Color And Ir Face Image Datasets
. -- Utility Of Facial Features
. -- Intelligent Face Detection
. -- Introduction
. -- Multilayer Perceptron Model
. -- Learning Algorithm
. -- Face Detection Networks
. -- Training Images
. -- Data Preparation
. -- Face Training
. -- Active Learning
. -- Exhaustive Training
. -- Evaluation Of Face Detection For Upright Faces
. -- Algorithm
. -- Image Scanning And Face Detection
. -- Real Time Face Detection
. -- Introduction
. -- Features
. -- Integral Image
. -- Rectangular Feature Calculation From Integral Image
. -- Adaboost
. -- Modified Adaboost Algorithm
. -- Cascade Classifier
. -- Face Detection Using Opencv
. -- Face Space Boundary Selection For Face Detection And Recognition
. -- Introduction
. -- Face Points, Face Classes And Face Space Boundaries
. -- Mathematical Preliminaries For Set Estimation Method
. -- Face Space Boundary Selection Using Set Estimation
. -- Algorithm For Global Threshold-Based Face Detection
. -- Experimental Design And Result Analysis
. -- Face/Non-Face Classification Using Global Threshold During Face Detection
. -- Comparison Between Threshold Selections By Rocbased And Set Estimation-Based Techniques
. -- Formation Of Training–Validation–Test Set
. -- Classification Of Face/Non-Face Regions
. -- Class Specific Thresholds Of Face-Class Boundaries For Face Recognition
. -- Experimental Design And Result Analysis
. -- Description Of Face Dataset
. -- Recognition Rates
. -- Open Test Results Considering Imposters In The System
. -- Recognition Rates Considering Only Clients In The System
. -- Evolutionary Design For Face Recognition
. -- Introduction
. -- Genetic Algorithms
. -- Implementation
. -- Algorithm
. -- Representation And Discrimination
. -- Whitening And Rotation Transformation
. -- Chromosome Representation And Genetic Operators
. -- The Fitness Functions
. -- The Evolutionary Pursuit Algorithm For Face Recognition
. -- Frequency Domain Correlation Filters In Face Recognition
. -- Introduction
. -- Psr Calculation
. -- A Brief Review On Correlation Filters
. -- Mathematical Background Of Correlation Filter
. -- Ecpsdf Filter Design
. -- Mace Filter Design
. -- Constrained Optimization With Lagrange Multipliers
. -- Mvsdf Filter Design
. -- Optimal Trade-Off (Otf) Filter Design
. -- Unconstrained Correlation Filter Design
. -- Mach Filter Design
. -- Umace Filter Design
. -- Otmach Filter Design
. -- Physical Requirements In Designing Correlation Filters
. -- Applications Of Correlation Filters
. -- Performance Analysis
. -- Performance Evaluation Using Psr Values
. -- Performance Evaluation In Terms Of %Rr And %Far
. -- Performance Evaluation By Receiver Operating Characteristics (Roc) Curves
. -- Video Correlation Filter
. -- Formulation Of Unconstrained Video Filter
. -- Mathematical Formulation Of Muotsdf
. -- Unconstrained Video Filter
. -- Distance Classifier Correlation Filter
. -- Application Of Uvf For Face Detection
. -- Training Approach
. -- Testing Approach
. -- Face Detection In Video Using Uvf
. -- Modification In Training Approach
. -- Validation Of Face Detection
. -- Face Classification Using Dccf
. -- Subspace Based Face Recognition In Frequency Domain
. -- Introduction
. -- Subspace-Based Correlation Filter
. -- Mathematical Modelling With 1D Subspace
. -- Reconstructed Correlation Filter Using 1D Subspace
. -- Optimum Projecting Image Correlation Filter Using 1D Subspace
. -- Face Classification And Recognition Analysis In Frequency Domain
. -- Test Results With 1D Subspace Analysis
. -- Comparative Study In Terms Of Psrs
. -- Comparative Study On %Rr And %Far
. -- Mathematical Modelling With 2D Subspace
. -- Reconstructed Correlation Filter Using 2D Subspace
. -- Test Results On 2D Subspace Analysis
. -- Psr Value Distribution For Authentic And Impostor Classes
. -- Comparative Performance In Terms Of %Rr
. -- Performance Evaluation Using Roc Analysis
. -- Class-Specific Nonlinear Correlation Filter
. -- Formulation Of Nonlinear Correlation Filters
. -- Nonlinear Optimum Projecting Image Correlation Filter
. -- Nonlinear Optimum Reconstructed Image Correlation Filter
. -- Face Recognition Analysis Using Correlation Classifiers
. -- Test Results
. -- Comparative Study On Discriminating Performances
. -- Comparative Performance Based On Psr Distribution
. -- Performance Analysis Using Roc
. -- Noise Sensitivity
. -- Landmark Localization For Face Recognition
. -- Introduction
. -- Elastic Bunch Graph Matching
. -- Gabor Wavelets
. -- Gabor Jets
. -- The Elastic Bunch Graph Matching Algorithm
. -- Application To Face Recognition
. -- Facial Landmark Detection
. -- Asef Correlation Filter
. -- Formulation Of Asef
. -- Eye Detection
. -- Multicorrelation Approach
. -- Design Of Landmark Filter(Lf)
. -- Landmark Localization With Localization Filter
. -- Test Results
. -- Two-Dimensional Synthetic Face Generation Using Set Estimation Technique
. -- Introduction
. -- Generating Face Points From Intraclass Face Images
. -- Face Generation Using Algorithm With Intraclass Features And Related Peak Signal To Noise Ratio
. -- Generating Face Points From Interclass Face Images
. -- Face Generation With Interclass Features
. -- Rejection Of The Non-Meaningful Face And Corresponding Psnr Test
. -- Generalization Capability Of Set Estimation Method
. -- Test Of Significance
. -- Datasets Of Face Images And Performance Tests For Face Recognition
. -- Face Datasets
. -- Orl Dataset
. -- Oulu Physics Dataset
. -- Xm2vts Dataset
. -- Yale Dataset
. -- Yale-B Dataset
. -- Mit Dataset
. -- Pie Dataset
. -- Umist Dataset
. -- Purdu Ar Dataset
. -- Feret Dataset
. -- Performance Evaluation Of Face Recognition Algorithms
. -- Feret And Xm2vts Protocols
. -- Face Recognition Grand Challenge (Frgc)
. -- Face Recognition Vendor Test (Frvt)
. -- Multiple Biometric Grand Challenge
. -- Focus Of Evaluation
. -- Conclusion
. -- Bibliography
. -- Index
TECNOLOGÍA
INGENIERÍA DE SISTEMAS
006.4.KUMA.00
Face Detection And Recognition Theory And Practice - 1A. ed - ESTADOS UNIDOS CRC PRESS 2016 - 325 23.5
Contents
. -- List Of Figures
. -- List Of Tables
. -- Preface
. -- Acknowledgment
. -- Introduction
. -- Introduction
. -- Biometric Identity Authentication Techniques
. -- Face As Biometric Identity
. -- Automated Face Recognition System
. -- Process Flow In Face Recognition System
. -- Problems Of Face Detection And Recognition
. -- Liveness Detection For Face Recognition
. -- Tests And Metrics
. -- Cognitive Psychology In Face Recognition
. -- Face Detection And Recognition Techniques
. -- Introduction To Face Detection
. -- Feature-Based Approaches For Face Detection
. -- Low-Level Analysis
. -- Edges
. -- Gray-Level Analysis
. -- Color Information In Face Detection
. -- Motion-Based Analysis
. -- Active Shape Model
. -- Feature Analysis
. -- Image-Based Approaches For Face Detection
. -- Statistical Approaches
. -- Face Recognition Methods
. -- Geometric Feature-Based Method
. -- Subspace-Based Face Recognition
. -- Neural Network-Based Face Recognition
. -- Correlation-Based Method
. -- Matching Pursuit-Based Methods
. -- Support Vector Machine Approach
. -- Selected Works On Face Classifiers
. -- Face Reconstruction Techniques
. -- Three-Dimensional Face Recognition
. -- Feature Extraction
. -- Global Feature Extraction
. -- Three-Dimensional Morphable Model
. -- Subspace Based Face Recognition
. -- Introduction
. -- Principal Component Analysis
. -- Two-Dimensional Principal Component Analysis
. -- Kernel Principal Component Analysis
. -- Fisher Linear Discriminant Analysis
. -- Fisher Linear Discriminant Analysis For Two-Class Case
. -- Independent Component Analysis
. -- Face Detection By Bayesian Approach
. -- Introduction
. -- Bayes Decision Rule For Classification
. -- Gaussian Distribution
. -- Bayes Theorem
. -- Bayesian Decision Boundaries And Discriminant Function
. -- Density Estimation Using Eigenspace Decomposition
. -- Bayesian Discriminant Feature Method
. -- Modelling Of Face And Non-Face Pattern
. -- Bayes Classification Using Bdf
. -- Experiments And Results
. -- Face Detection In Color And Infrared Images
. -- Introduction
. -- Face Detection In Color Images
. -- Color Spaces
. -- Rgb Model
. -- Hsi Color Model
. -- Ycbcr Color Space
. -- Face Detection From Skin Regions
. -- Skin Modelling
. -- Skin Color Modelling Explicitly From Rgb Space
. -- Skin Color Modelling Explicitly From Ycbcr Space
. -- Probabilistic Skin Detection
. -- Face Detection By Localizing Facial Features
. -- Eyemap
. -- Mouthmap
. -- Face Detection In Infrared Images
. -- Multivariate Histogram-Based Image Segmentation
. -- Method For Finding Major Clusters From a Multivariate Histogram
. -- Experiments And Results On The Color And Ir Face Image Datasets
. -- Utility Of Facial Features
. -- Intelligent Face Detection
. -- Introduction
. -- Multilayer Perceptron Model
. -- Learning Algorithm
. -- Face Detection Networks
. -- Training Images
. -- Data Preparation
. -- Face Training
. -- Active Learning
. -- Exhaustive Training
. -- Evaluation Of Face Detection For Upright Faces
. -- Algorithm
. -- Image Scanning And Face Detection
. -- Real Time Face Detection
. -- Introduction
. -- Features
. -- Integral Image
. -- Rectangular Feature Calculation From Integral Image
. -- Adaboost
. -- Modified Adaboost Algorithm
. -- Cascade Classifier
. -- Face Detection Using Opencv
. -- Face Space Boundary Selection For Face Detection And Recognition
. -- Introduction
. -- Face Points, Face Classes And Face Space Boundaries
. -- Mathematical Preliminaries For Set Estimation Method
. -- Face Space Boundary Selection Using Set Estimation
. -- Algorithm For Global Threshold-Based Face Detection
. -- Experimental Design And Result Analysis
. -- Face/Non-Face Classification Using Global Threshold During Face Detection
. -- Comparison Between Threshold Selections By Rocbased And Set Estimation-Based Techniques
. -- Formation Of Training–Validation–Test Set
. -- Classification Of Face/Non-Face Regions
. -- Class Specific Thresholds Of Face-Class Boundaries For Face Recognition
. -- Experimental Design And Result Analysis
. -- Description Of Face Dataset
. -- Recognition Rates
. -- Open Test Results Considering Imposters In The System
. -- Recognition Rates Considering Only Clients In The System
. -- Evolutionary Design For Face Recognition
. -- Introduction
. -- Genetic Algorithms
. -- Implementation
. -- Algorithm
. -- Representation And Discrimination
. -- Whitening And Rotation Transformation
. -- Chromosome Representation And Genetic Operators
. -- The Fitness Functions
. -- The Evolutionary Pursuit Algorithm For Face Recognition
. -- Frequency Domain Correlation Filters In Face Recognition
. -- Introduction
. -- Psr Calculation
. -- A Brief Review On Correlation Filters
. -- Mathematical Background Of Correlation Filter
. -- Ecpsdf Filter Design
. -- Mace Filter Design
. -- Constrained Optimization With Lagrange Multipliers
. -- Mvsdf Filter Design
. -- Optimal Trade-Off (Otf) Filter Design
. -- Unconstrained Correlation Filter Design
. -- Mach Filter Design
. -- Umace Filter Design
. -- Otmach Filter Design
. -- Physical Requirements In Designing Correlation Filters
. -- Applications Of Correlation Filters
. -- Performance Analysis
. -- Performance Evaluation Using Psr Values
. -- Performance Evaluation In Terms Of %Rr And %Far
. -- Performance Evaluation By Receiver Operating Characteristics (Roc) Curves
. -- Video Correlation Filter
. -- Formulation Of Unconstrained Video Filter
. -- Mathematical Formulation Of Muotsdf
. -- Unconstrained Video Filter
. -- Distance Classifier Correlation Filter
. -- Application Of Uvf For Face Detection
. -- Training Approach
. -- Testing Approach
. -- Face Detection In Video Using Uvf
. -- Modification In Training Approach
. -- Validation Of Face Detection
. -- Face Classification Using Dccf
. -- Subspace Based Face Recognition In Frequency Domain
. -- Introduction
. -- Subspace-Based Correlation Filter
. -- Mathematical Modelling With 1D Subspace
. -- Reconstructed Correlation Filter Using 1D Subspace
. -- Optimum Projecting Image Correlation Filter Using 1D Subspace
. -- Face Classification And Recognition Analysis In Frequency Domain
. -- Test Results With 1D Subspace Analysis
. -- Comparative Study In Terms Of Psrs
. -- Comparative Study On %Rr And %Far
. -- Mathematical Modelling With 2D Subspace
. -- Reconstructed Correlation Filter Using 2D Subspace
. -- Test Results On 2D Subspace Analysis
. -- Psr Value Distribution For Authentic And Impostor Classes
. -- Comparative Performance In Terms Of %Rr
. -- Performance Evaluation Using Roc Analysis
. -- Class-Specific Nonlinear Correlation Filter
. -- Formulation Of Nonlinear Correlation Filters
. -- Nonlinear Optimum Projecting Image Correlation Filter
. -- Nonlinear Optimum Reconstructed Image Correlation Filter
. -- Face Recognition Analysis Using Correlation Classifiers
. -- Test Results
. -- Comparative Study On Discriminating Performances
. -- Comparative Performance Based On Psr Distribution
. -- Performance Analysis Using Roc
. -- Noise Sensitivity
. -- Landmark Localization For Face Recognition
. -- Introduction
. -- Elastic Bunch Graph Matching
. -- Gabor Wavelets
. -- Gabor Jets
. -- The Elastic Bunch Graph Matching Algorithm
. -- Application To Face Recognition
. -- Facial Landmark Detection
. -- Asef Correlation Filter
. -- Formulation Of Asef
. -- Eye Detection
. -- Multicorrelation Approach
. -- Design Of Landmark Filter(Lf)
. -- Landmark Localization With Localization Filter
. -- Test Results
. -- Two-Dimensional Synthetic Face Generation Using Set Estimation Technique
. -- Introduction
. -- Generating Face Points From Intraclass Face Images
. -- Face Generation Using Algorithm With Intraclass Features And Related Peak Signal To Noise Ratio
. -- Generating Face Points From Interclass Face Images
. -- Face Generation With Interclass Features
. -- Rejection Of The Non-Meaningful Face And Corresponding Psnr Test
. -- Generalization Capability Of Set Estimation Method
. -- Test Of Significance
. -- Datasets Of Face Images And Performance Tests For Face Recognition
. -- Face Datasets
. -- Orl Dataset
. -- Oulu Physics Dataset
. -- Xm2vts Dataset
. -- Yale Dataset
. -- Yale-B Dataset
. -- Mit Dataset
. -- Pie Dataset
. -- Umist Dataset
. -- Purdu Ar Dataset
. -- Feret Dataset
. -- Performance Evaluation Of Face Recognition Algorithms
. -- Feret And Xm2vts Protocols
. -- Face Recognition Grand Challenge (Frgc)
. -- Face Recognition Vendor Test (Frvt)
. -- Multiple Biometric Grand Challenge
. -- Focus Of Evaluation
. -- Conclusion
. -- Bibliography
. -- Index
TECNOLOGÍA
INGENIERÍA DE SISTEMAS
006.4.KUMA.00