The purpose of this book, entitled Face Analysis, Modeling and Recognition Systems is to provide a concise and comprehensive coverage of artificial face recognition domain across four major areas of interest: biometrics, robotics, image databases and cognitive models. Our book aims to provide the reader with current state-of-the-art in these domains. The book is composed of 12 chapters which are grouped in four sections. The chapters in this book describe numerous novel face analysis techniques and approach many unsolved issues. The authors who contributed to this book work as professors and researchers at important institutions across the globe, and are recognized experts in the scientific fields approached here. The topics in this book cover a wide range of issues related to face analysis and here are offered many solutions to open issues. We anticipate that this book will be of special interest to researchers and academics interested in computer vision, biometrics, image processing, pattern recognition and medical diagnosis.

3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. The book covers face acquisition through 3D scanners and 3D face pre-processing, before examining the three main approaches for 3D facial surface analysis and recognition: facial curves; facial surface features; and 3D morphable models. Whilst the focus of these chapters is fundamentals and methodologies, the algorithms provided are tested on facial biometric data, thereby continually showing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply these mathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications including biometrics, forensic applications, facial expression analysis, and model fitting to 2D images • Contains numerous exercises and algorithms throughout the book

"Face recognition is a type of biometric software application that can identify a specific individual in a digital image by analysing and comparing patterns. A facial recognition system is a computer application capable of identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. Facial recognition systems are commonly used for security purposes but are increasingly being used in a variety of other applications. In addition to being used for security systems, establishments have found a number of other applications for facial recognition systems. Some facial recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face. For instance, an algorithm may analyse the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition. A probe image is then compared with the face data. One of the earliest successful systems is based on template matching techniques applied to a set of salient facial features, providing a sort of compressed face representation. The book named Face Analysis, Modeling and Recognition Systems offers a concise and inclusive analysis of artificial face recognition domain through major areas of interest: biometrics, robotics, image databases and cognitive models. The topics in this book describe numerous novel face analysis techniques and approach many unsolved issues. It will be of special interest to academics and researchers interested in computer vision, biometrics, image processing, pattern recognition and medical diagnosis."

The purpose of this book, entitled Face Analysis, Modeling and Recognition Systems is to provide a concise and comprehensive coverage of artificial face recognition domain across four major areas of interest: biometrics, robotics, image databases and cognitive models. Our book aims to provide the reader with current state-of-the-art in these domains. The book is composed of 12 chapters which are grouped in four sections. The chapters in this book describe numerous novel face analysis techniques and approach many unsolved issues. The authors who contributed to this book work as professors and researchers at important institutions across the globe, and are recognized experts in the scientific fields approached here. The topics in this book cover a wide range of issues related to face analysis and here are offered many solutions to open issues. We anticipate that this book will be of special interest to researchers and academics interested in computer vision, biometrics, image processing, pattern recognition and medical diagnosis.

This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems; provides comprehensive coverage of face detection, tracking, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications; contains numerous step-by-step algorithms; describes a broad range of applications; presents contributions from an international selection of experts; integrates numerous supporting graphs, tables, charts, and performance data.

This book seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor. These include neurosciences, statistics, signal and image processing, computer vision, machine learning and data mining. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development. The book’s focused approach and its clarity of presentation make this an excellent reference work.

"This authoritative handbook is the first to provide complete coverage of face recognition, including major established approaches, algorithms, systems, databases, evaluation methods, and applications. After a thorough introductory chapter from the editors, 15 chapters address the sub-areas and major components necessary for designing operational face recognition systems. Each chapter focuses on a specific topic, reviewing background information, reviewing up-to-date techniques, presenting results, and offering challenges and future directions." "This accessible, practical reference is an essential resource for scientists and engineers, practitioners, government officials, and students planning to work in image processing, computer vision, biometrics and security, Internet communications, computer graphics, animation, and the computer game industry."--BOOK JACKET.

This book constitutes the refereed proceedings of the Third International Workshop on Analysis and Modelling of Faces and Gestures, AMFG 2007, held within the scope of ICCV 2007, the International Conference on Computer Vision. The papers review the status of recognition, analysis and modeling of face, gesture, activity, and behavior. Topics addressed include feature representation, 3D face, video-based face recognition, facial motion analysis, and sign recognition.

Face Recognition: Cognitive and Computational Processes critically discusses current research in face recognition, leading to an original approach with criminological applications. The book covers • The methodological and philosophical basis of research in face recognition. • Findings and their explanations, conceptual issues, theories and models of face recognition • The Catch Model (Rakover & Cahlon) for reconstructing (identifying) a face from memory, and other models and methods of face reconstruction. • Conscious perception and recognition of faces. The book also discusses original ideas on conceptualizing face perception and recognition in tasks of facial cognition, developing the Schema Theory and the Catch Model, and introducing Rakover & Cahlon's discovery of the proposed law of Face Recognition by Similarity (FRBS). (Series B)

Face recognition is one of the most important abilities for everyday social interactions. Congenital prosopagnosia, also referred to as "face blindness", describes the innate, lifelong impairment to recognize other people by their face. About 2 % of the population is affected. This thesis aimed to investigate different aspects of face processing in prosopagnosia in order to gain a clearer picture and a better understanding of this heterogeneous impairment. In a first study, various aspects of face recognition and perception were investigated to allow for a better understanding of the nature of prosopagnosia. The results replicated previous findings and helped to resolve discrepancies between former studies. In addition, it was found that prosopagnosics show an irregular response behavior in tests for holistic face recognition. We propose that prosopagnosics either switch between strategies or respond randomly when performing these tests. In a second study, the general face recognition deficit observed in prosopagnosia was compared to face recognition deficits occurring when dealing with other-race faces. Most humans find it hard to recognize faces of an unfamiliar race, a phenomenon called the "other-race effect". The study served to investigate if there is a possible common mechanism underlying prosopagnosia and the other-race effect, as both are characterized by problems in recognizing faces. The results allowed to reject this hypothesis, and yielded new insights about similarities and dissimilarities between prosopagnosia and the other-race effect. In the last study, a possible treatment of prosopagnosia was investigated. This was based on a single case in which a prosopagnosic reported a sudden improvement of her face recognition abilities after she started a special diet. The different studies cover diverse aspects of prosopagnosia: the nature of prosopagnosia and measurement of its characteristics, comparison to other face recognition impairments, and treatment options. The results serve to broaden the knowledge about prosopagnosia and to gain a more detailed picture of this impairment.