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Face recognition has received substantial attention from researchers in biometrics, computer vision, pattern recognition, and cognitive psychology communities because of the increased attention being devoted to security, man-machine communication, content-based image retrieval, and image/video coding. We have proposed two automated recognition paradigms to advance face recognition technology. Three major tasks involved in face recognition systems are: (i) face detection, (ii) face modeling, and (iii) face matching. We have developed a face detection algorithm for color images in the presence of various lighting conditions as well as complex backgrounds. Our detection method first corrects the color bias by a lighting compensation technique that automatically estimates the parameters of reference white for color correction. We overcame the difficulty of detecting the low-luma and high-luma skin tones by applying a nonlinear transformation to the Y CbCr color space. Our method generates face candidates based on the spatial arrangement of detected skin patches. We constructed eye, mouth, and face boundary maps to verify each face candidate. Experimental results demonstrate successful detection of faces with different sizes, color, position, scale, orientation, 3D pose, and expression in several photo collections. 3D human face models augment the appearance-based face recognition approaches to assist face recognition under the illumination and head pose variations. For the two proposed recognition paradigms, we have designed two methods for modeling human faces based on (i) a generic 3D face model and an individual's facial measurements of shape and texture captured in the frontal view, and (ii) alignment of a semantic face graph, derived from a generic 3D face model, onto a frontal face image.
This book constitutes the refereed proceedings of the 5th International Conference on Audio- and Video-Based Biometric Person Authentication, AVBPA 2005, held in Hilton Rye Town, NY, USA, in July 2005. The 66 revised oral papers and 50 revised poster papers presented were carefully reviewed and selected from numerous submissions. The papers discuss all aspects of biometrics including iris, fingerprint, face, palm print, gait, gesture, speaker, and signature; theoretical and algorithmic issues are dealt with as well as systems issues. The industrial side of biometrics is evident from presentations on smart cards, wireless devices, and architectural and implementation aspects.
Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are acquired from a distance. It examines both model-free and model-based approaches to gait-based human recognition, including newly developed techniques where the both the model and the data (obtained from multiple cameras) are in 3D. In addition, the work considers new video-based techniques for face profile recognition, and for the super-resolution of facial imagery obtained at different angles. Finally, the book investigates integrated systems that detect and fuse both gait and face biometrics from video data. Topics and features: discusses a framework for human gait analysis based on Gait Energy Image, a spatio-temporal gait representation; evaluates the discriminating power of model-based gait features using Bayesian statistical analysis; examines methods for human recognition using 3D gait biometrics, and for moving-human detection using both color and thermal image sequences; describes approaches for the integration face profile and gait biometrics, and for super-resolution of frontal and side-view face images; introduces an objective non-reference quality evaluation algorithm for super-resolved images; presents performance comparisons between different biometrics and different fusion methods for integrating gait and super-resolved face from video. This unique and authoritative text is an invaluable resource for researchers and graduate students of computer vision, pattern recognition and biometrics. The book will also be of great interest to professional engineers of biometric systems.
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
Human faces are familiar to our visual systems. We easily recognize a person's face in arbitrary lighting conditions and in a variety of poses; detect small appearance changes; and notice subtle expression details. Can computer vision systems process face images as well as human vision systems can? Face image processing has potential applications in surveillance, image and video search, social networking and other domains. A comprehensive guide to this fascinating topic, this book provides a systematic description of modeling face geometry and appearance from images, including information on mathematical tools, physical concepts, image processing and computer vision techniques, and concrete prototype systems. The book will be an excellent reference for researchers and graduate students in computer vision, computer graphics and multimedia, as well as application developers who would like to gain a better understanding of the state of the art.
Automatic personal authentication using biometric information is becoming more essential in applications of public security, access control, forensics, banking, etc. Many kinds of biometric authentication techniques have been developed based on different biometric characteristics. However, most of the physical biometric recognition techniques are based on two dimensional (2D) images, despite the fact that human characteristics are three dimensional (3D) surfaces. Recently, 3D techniques have been applied to biometric applications such as 3D face, 3D palmprint, 3D fingerprint, and 3D ear recognition. This book introduces four typical 3D imaging methods, and presents some case studies in the field of 3D biometrics. This book also includes many efficient 3D feature extraction, matching, and fusion algorithms. These 3D imaging methods and their applications are given as follows: - Single view imaging with line structured-light: 3D ear identification - Single view imaging with multi-line structured-light: 3D palmprint authentication - Single view imaging using only 3D camera: 3D hand verification - Multi-view imaging: 3D fingerprint recognition 3D Biometrics: Systems and Applications is a comprehensive introduction to both theoretical issues and practical implementation in 3D biometric authentication. It will serve as a textbook or as a useful reference for graduate students and researchers in the fields of computer science, electrical engineering, systems science, and information technology. Researchers and practitioners in industry and R&D laboratories working on security system design, biometrics, immigration, law enforcement, control, and pattern recognition will also find much of interest in this book.
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
Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities
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.