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Full Description
Major strides have been made in face processing in the last ten years due to the fast growing need for security in various locations around the globe. A human eye can discern the details of a specific face with relative ease. It is this level of detail that researchers are striving to create with ever evolving computer technologies that will become our perfect mechanical eyes. The difficulty that confronts researchers stems from turning a 3D object into a 2D image. That subject is covered in depth from several different perspectives in this volume.Face Processing: Advanced Modeling and Methods begins with a comprehensive introductory chapter for those who are new to the field. A compendium of articles follows that is divided into three sections. The first covers basic aspects of face processing from human to computer. The second deals with face modeling from computational and physiological points of view. The third tackles the advanced methods, which include illumination, pose, expression, and more. Editors Zhao and Chellappa have compiled a concise and necessary text for industrial research scientists, students, and professionals working in the area of image and signal processing.
Contents
PrefacePART I: THE BASICSChapter 1: A Guided Tour for Face ProcessingChapter 2: Eigenface and BeyondChapter 3: Statistical Evaluation of Face Recognition SystemsPART II: FACE MODELINGChapter 4: 3D Morphable Face Model: A Unified Approach for Analysis and Synthesis of ImagesChapter 5: Expression-Invariant Three-Dimensional Face RecognitionChapter 6: 3D Face Modeling from Monocular Video SequencesChapter 7: Face Modeling by Information MaximizationChapter 8: Face Recognition by HumanChapter 9: Predicting Face Recognition Success for HumansChapter 10: Distributed Representation of Faces and ObjectsPART III: ADVANCED METHODSChapter 11: On the Effect of Illumination and Face RecognitionChapter 12: Modeling Illumination Variation with Spherical HarmonicsChapter 13: Multi-Subregion Based Probabilistic Approach Toward Pose-Invariant Face Recognition Chapter 14:Morphable Models for Training a Component-Based Face Recognition SystemChapter 15: Model-Based Face Modeling and Tracking with Application to Video ConferencingChapter 16: 3D and MultiModal 3D & 2D Face RecognitionChapter 17: Beyond One Still Image: Face Recognition from multiple Still Images or Video SequenceChapter 18: Subset Modeling of Face Localization Error, Occlusion and ExpressionChapter 19: Real-Time Robust Face and Facial Features Detection with Information-Based Maximum DiscriminationChapter 20: Current Landscape of Thermal Infrared Face RecognitionChapter 21: Multimodal Biometrics: Augmenting Face with Other Cues
