Face Processing: Advanced Modeling and Methods

Prof. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from Indian Institute of Science, Bangalore, in 1977. He received M.S.E.E. and Ph.D. Degrees in Electrical Engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981-1986) and Associate Professor (1986-1991) and Director of the Signal and Image Processing Institute (1988-1990) at University of Southern California, Los Angeles. Over the last 29 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has co-authored and edited books on MRFs, face and gait recognition and collected works on image processing and analysis. His current research interests are face and gait analysis, markerless motion capture, 3D modeling from video, image and video-based recognition and exploitation and hyper spectral processing.

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