| Description |
1 online resource (264 pages) : illustrations, tables |
| Contents |
FOREWORD ; PREFACE ; LIST OF CONTRIBUTORS ; Facial Expression Classification Based on Convolutional Neural Networks ; INTRODUCTION; Convolutional Neural Networks; Facial Expression Analysis; GRADIENT-BASED LEARNING FOR CNNS; FEATURE GENERALIZATION; EXPERIMENTS; Datasets; CK-Regianini Dataset; CK-Zheng Dataset; CMU-Pittsburgh dataset ; Experiments on CNN-based Facial Expression Classification; Design; Results and Analysis; Experiments on Feature Generalization; Design; Results and Analysis; DISCUSSION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES |
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Sparsity Preserving Projection Based Constrained Graph Embedding and Its Application to Face Recognition INTRODUCTION; RELATED WORK; Locality Preserving Projection; Neighborhood Preserving Embedding; Sparsity Preserving Projection; Constrained Graph Embedding; SPP BASED CONSTRAINED GRAPH EMBEDDING; SPP-CGE; Out-of-Sample Extension; EXPERIMENTAL RESULTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Face Recognition Using Exponential Local Discriminant Embedding ; INTRODUCTION; Contribution and Related Work; REVIEW OF LOCAL DISCRIMINANT EMBEDDING (LDE) |
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Intrinsic Graph and Penalty GraphOptimal Mapping; The Small Sample Size Problem; EXPONENTIAL LDE; Matrix Exponential; Exponential LDE; THEORETICAL ANALYSIS OF ELDE; Solving the SSS Problem; Distance Diffusion Mapping; PERFORMANCE EVALUATION; Face Databases; Recognition Accuracy; Comparison between Regularized LDE and ELDE; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; Adaptive Locality Preserving Projections for Face Recognition ; INTRODUCTION; LOCALITY PRESERVING PROJECTIONS; ENHANCED AND PARAMETERLESS LPP; PERFORMANCE EVALUATION; Face Databases; Experimental Results |
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Performance Comparison for OLPP and SLPPCONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; Face Recognition Using 3D Face Rectification ; INTRODUCTION; PROPOSED METHOD ; FACE DATABASE ; PREPROCESSING ; FACIAL FEATURE DETECTION ; POSE ESTIMATION; IRAD Contours; Ellipse Fitting And Roll Correction; Yaw Correction; Pitch Correction; Accuracy Of The Pose Estimation Method; ROTATION AND POST PROCESSING; EXPERIMENTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; 3D Face Recognition ; INTRODUCTION; 3D FACE ACQUISITION; 3D FACE REPRESENTATION; PREPROCESSING |
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3D FACE ALIGNMENTFACE RECOGNITION; CONCLUDING REMARKS; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Model-Less 3D Face Pose Estimation ; INTRODUCTION; STATE OF THE ART; THE MACHINE LEARNING METHODOLOGY; Locality Preserving Projections; LPP Algorithm; Supervised Locality Preserving Projections; LABEL-SENSITIVE LOCALITY PRESERVING PROJECTION; Presetting:; Algorithm:; PROPOSED APPROACH: SPARSE GRAPH BASED LSLPP; EXPERIMENTAL RESULTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Efficient Deformable 3D Face Model Fitting to Monocular Images ; INTRODUCTION |
| Summary |
Annotation Advances in Face Image Analysis: Theory and applications describes several approaches to facial image analysis and recognition. Eleven chapters cover advances in computer vision and pattern recognition methods used to analyze facial data. The topics addre |
| Bibliography |
Includes bibliographical references at the end of each chapters and index |
| Notes |
Online resource; title from PDF title page (ebrary, viewed May 3, 2016) |
| Subject |
Human face recognition (Computer science)
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COMPUTERS -- General.
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Human face recognition (Computer science)
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| Form |
Electronic book
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| Author |
Dornaika, Fadi, editor
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Assoum, Ammar, contributor
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| ISBN |
9781681081106 |
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1681081105 |
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