000			00619nam a2200193Ia 4500
999			_c63198 _d63193
003			OSt
005			20181023043908.0
008			24418b pe ||||| |||| 00| 0 spa d
040			_cTranscribing agency
082			_a006.4.KUMA.00
100			_aKumar Datta, Asit
100			_eAutor
245		0	_aFace Detection And Recognition Theory And Practice
250			_a1A. ed
260			_aESTADOS UNIDOS
260			_bCRC PRESS
260			_c2016
300			_a325
300			_c23.5
505			_aContents . -- 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
650			_aTECNOLOGÍA
650			_aINGENIERÍA DE SISTEMAS
700			_aDatta, Madhura
700			_aKumar Banerjee, Pradipta
942			_cTM001 _2ddc