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Face Detection And Recognition Theory And Practice

Por: Kumar Datta, Asit | [Autor].
Colaborador(es): Datta, Madhura | Kumar Banerjee, Pradipta.
Editor: ESTADOS UNIDOS ; CRC PRESS ; 2016Edición: 1A. ed.Descripción: 325; 23.5.Tema(s): TECNOLOGÍA | INGENIERÍA DE SISTEMASClasificación CDD: 006.4.KUMA.00
Contenidos:
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
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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

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