Advances in face image analysis : theory and application / edited by Fadi Dornaika ; contributors Ammar Assoum [and fifteen others].

Format:

Book

Author/Creator:

Dornaika, Fadi, Author.

Contributor:

Dornaika, Fadi, editor.

Assoum, Ammar, contributor.

Language:

English

Subjects (All):

Human face recognition (Computer science).

Physical Description:

1 online resource (264 p.)

Edition:

1st ed.

Place of Publication:

Sharjah, United Arab Emirates : Bentham Science Publishers, 2016.

Summary:

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 addressed in this book include automatic face detection 3D face model fitting robust face recognition facial expression recognition face image data embedding model-less 3D face pose estimation and image-based age estimation. The chapters are also written by experts from a different research groups. Readers will therefore have access to contemporary knowledge on facial recognition with some diverse perspectives offered for individual techniques. The book is a useful resource for a wide audience such as i) researchers and professionals working in the field of face image analysis ii) the entire pattern recognition community interested in processing and extracting features from raw face images and iii) technical experts as well as postgraduate computer science students interested in cutting edge concepts of facial image recognition.

Contents:

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

LIGHTWEIGHT FACIAL FEATURE DETECTION

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters and index.

Description based on online resource; title from PDF title page (ebrary, viewed May 3, 2016).

ISBN:

9781681081106

1681081105

OCLC:

948924362