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Advances in face image analysis : theory and applications.

Author: Fadi Dornaika.
Publisher: [Place of publication not identified] : Bentham Science Publisher
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Dornaika, Fadi.
Advances in Face Image Analysis: Theory and Application.
Sharjah : Bentham Science Publishers, ©2016
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Fadi Dornaika.
ISBN: 1681081105 9781681081106
OCLC Number: 948547025
Description: 1 online resource
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. 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). 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. 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. 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.

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