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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
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. - Contributions from over 35 leading experts in face detection, recognition and image processing - Over 150 informative images with 16 images in FULL COLOR illustrate and offer insight into the most up-to-date advanced face processing methods and techniques - Extensive detail makes this a need-to-own book for all involved with image and signal processing
The aim of this book is to deal with biometrics in terms of signal and image processing methods and algorithms. This will help engineers and students working in digital signal and image processing deal with the implementation of such specific algorithms. It discusses numerous signal and image processing techniques that are very often used in biometric applications. In particular, algorithms related to hand feature extraction, speech recognition, 2D/3D face biometrics, video surveillance and other interesting approaches are presented. Moreover, in some chapters, Matlab codes are provided so that readers can easily reproduce some basic simulation results. This book is suitable for final-year undergraduate students, postgraduate students, engineers and researchers in the field of computer engineering and applied digital signal and image processing. 1. Introduction to Biometrics, Bernadette Dorizzi. 2. Introduction to 2D Face Recognition, Amine Nait-Ali and Dalila Cherifi. 3. Facial Soft Biometrics for Person Recognition, Antitza Dantcheva, Christelle Yemdji, Petros Elia and Jean-Luc Dugelay. 4. Modeling, Reconstruction and Tracking for Face Recognition, Catherine Herold, Vincent Despiegel, Stéphane Gentric, Séverine Dubuisson and Isabelle Bloch. 5. 3D Face Recognition, Mohsen Ardabilian, Przemyslaw Szeptycki, Di Huang and Liming Chen. 6. Introduction to Iris Biometrics, Kamel Aloui, Amine Nait-Ali, Régis Fournier and Saber Naceur. 7. Voice Biometrics: Speaker Verification and Identification, Foezur Chowdhury, Sid-Ahmed Selouani and Douglas O’Shaughnessy. 8. Introduction to Hand Biometrics, Régis Fournier and Amine Nait-Ali. 9. Multibiometrics, Romain Giot, Baptiste Hemery, Estelle Cherrier and Christophe Rosenberger. 10. Hidden Biometrics, Amine Nait-Ali, Régis Fournier, Kamel Aloui and Noureddine Belgacem. 11. Performance Evaluation of Biometric Systems, Mohamad El-Abed, Romain Giot, Baptiste Hemery, Julien Mahier and Christophe Rosenberger. 12. Classification Techniques for Biometrics, Amel Bouchemha, Chérif Nait-Hamoud, Amine Nait-Ali and Régis Fournier. 13. Data Cryptography, Islam Naveed and William Puech. 14. Visual Data Protection, Islam Naveed and William Puech. 15. Biometrics in Forensics, Guillaume Galou and Christophe Lambert.
This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning.Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.
This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.
Biometrics-Unique and Diverse Applications in Nature, Science, and Technology provides a unique sampling of the diverse ways in which biometrics is integrated into our lives and our technology. From time immemorial, we as humans have been intrigued by, perplexed by, and entertained by observing and analyzing ourselves and the natural world around us. Science and technology have evolved to a point where we can empirically record a measure of a biological or behavioral feature and use it for recognizing patterns, trends, and or discrete phenomena, such as individuals' and this is what biometrics is all about. Understanding some of the ways in which we use biometrics and for what specific purposes is what this book is all about.
This book constitutes the refereed proceedings of the 5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004, held in Guanzhou, China in December 2004. The 60 revised full papers presented together with 14 invited papers by internationally leading researchers were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on biometrics, best performing biometric engines, face localization, pose estimation, face recognition, 3D based methods, subspace and discriminant analysis, systems and applications, fingerprint preprocessing and minutiae extraction, fingerprint recognition and matching, fingerprint classificaiton, iris recognition, speaker recognition, and other biometric primitives.
This book constitutes the refereed proceedings of the 11th Chinese Conference on Biometric Recognition, CCBR 2016, held in Chengdu, China, in October 2016. The 84 revised full papers presented in this book were carefully reviewed and selected from 138 submissions. The papers focus on Face Recognition and Analysis; Fingerprint, Palm-print and Vascular Biometrics; Iris and Ocular Biometrics; Behavioral Biometrics; Affective Computing; Feature Extraction and Classification Theory; Anti-Spoofing and Privacy; Surveillance; and DNA and Emerging Biometrics.
The LNCS volume 12878 constitutes the proceedings of the 15th Chinese Conference on Biometric Recognition, held in Shanghai, China, in September 2021. The 53 papers presented in this book were carefully reviewed and selected from 72 submissions. The papers cover a wide range of topics such as multi-modal biometrics and emerging biometrics; hand biometrics; facial biometrics; and speech biometrics.
This book provides ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field. It offers students and software engineers a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits, its main emphasis is placed on multi-sensory and multi-modal face biometrics algorithms and systems.