Towards Robust And Secure Face Recognition
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Towards Robust And Secure Face Recognition
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Author : Debayan Deb
language : en
Publisher:
Release Date : 2021
Towards Robust And Secure Face Recognition written by Debayan Deb and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic dissertations categories.
The accuracy, usability, and touchless acquisition of state-of-the-art automated face recognition systems (AFR) have led to their ubiquitous adoption in a plethora of domains, including mobile phone unlock, access control systems, and payment services. Despite impressive recognition performance, prevailing AFR systems remain vulnerable to the growing threat of face attacks which can be launched in both physical and digital domains. Face attacks can be broadly classified into three attack categories: (i) Spoof attacks: artifacts in the physical domain (e.g., 3D masks, eye glasses, replaying videos), (ii) Adversarial attacks: imperceptible noises added to probes for evading AFR systems, and (iii) Digital manipulation attacks: entirely or partially modified photo-realistic faces using generative models. Each of these categories is composed of different attack types. For example, each spoof medium, e.g., 3D mask and makeup, constitutes one attack type. Likewise, in adversarial and digital manipulation attacks, each attack model, designed by unique objectives and losses, may be considered as one attack type. Thus, the attack categories and types form a 2-layer tree structure encompassing the diverse attacks. Such a tree will inevitably grow in the future. Given the growing dissemination of "fake news" and "deepfakes", the research community and social media platforms alike are pushing towards generalizable defense against continuously evolving and sophisticated face attacks. In this dissertation, we first propose a set of defense methods that achieve state-of-the-art performance in detecting attack types within individual attack categories, both physical (e.g., face spoofs) and digital (e.g., adversarial faces and digital manipulation), then introduce a method for simultaneously safeguarding against each attack.First, in an effort to impart generalizability and interpretability to face spoof detection systems, we propose a new face anti-spoofing framework specifically designed to detect unknown spoof types, namely, Self-Supervised Regional Fully Convolutional Network (SSR-FCN), that is trained to learn local discriminative cues from a face image in a self-supervised manner. The proposed framework improves generalizability while maintaining the computational efficiency of holistic face anti-spoofing approaches (
Diana Mogensen
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Author :
language : en
Publisher:
Release Date :
Diana Mogensen written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Artists, Australian categories.
Reliable Face Recognition Methods
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Author : Harry Wechsler
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-05
Reliable Face Recognition Methods written by Harry Wechsler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-05 with Computers categories.
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.
Handbook Of Face Recognition
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Author : Stan Z. Li
language : en
Publisher: Springer Nature
Release Date : 2024-01-30
Handbook Of Face Recognition written by Stan Z. Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-30 with Computers categories.
The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. 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 recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, 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 from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.
Towards A Robust Unconstrained Face Recognition Pipeline With Deep Neural Networks
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Author : Yichun Shi
language : en
Publisher:
Release Date : 2021
Towards A Robust Unconstrained Face Recognition Pipeline With Deep Neural Networks written by Yichun Shi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic dissertations categories.
Face recognition is a classic problem in the field of computer vision and pattern recognition due to its wide applications in real-world problems such as access control, identity verification, physical security, surveillance, etc. Recent progress in deep learning techniques and the access to large-scale face databases has lead to a significant improvement of face recognition accuracy under constrained and semi-constrained scenarios. Deep neural networks are shown to surpass human performance on Labeled Face in the Wild (LFW), which consists of celebrity photos captured in the wild. However, in many applications, e.g. surveillance videos, where we cannot assume that the presented face is under controlled variations, the performance of current DNN-based methods drop significantly. The main challenges in such an unconstrained face recognition problem include, but are not limited to: lack of labeled data, robust face normalization, discriminative representation learning and the ambiguity of facial features caused by information loss.In this thesis, we propose a set of methods that attempt to address the above challenges in unconstrained face recognition systems. Starting from a classic deep face recognition pipeline, we review how each step in this pipeline could fail on low-quality uncontrolled input faces, what kind of solutions have been studied before, and then introduce our proposed methods. The various methods proposed in this thesis are independent but compatible with each other. Experiment on several challenging benchmarks, e.g. IJB-C and IJB-S show that the proposed methods are able to improve the robustness and reliability of deep unconstrained face recognition systems. Our solution achieves state-of-the-art performance, i.e. 95.0% TAR FAR=0.001% on IJB-C dataset and 61.98% Rank1 retrieval rate on the surveillance-to-booking protocol of IJB-S dataset.
Face Recognition Across The Imaging Spectrum
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Author : Thirimachos Bourlai
language : en
Publisher: Springer
Release Date : 2016-02-12
Face Recognition Across The Imaging Spectrum written by Thirimachos Bourlai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-12 with Computers categories.
This authoritative text/reference presents a comprehensive review of algorithms and techniques for face recognition (FR), with an emphasis on systems that can be reliably used in operational environments. Insights are provided by an international team of pre-eminent experts into the processing of multispectral and hyperspectral face images captured under uncontrolled environments. These discussions cover a variety of imaging sensors ranging from state-of-the-art visible and infrared imaging sensors, to RGB-D and mobile phone image sensors. A range of different biometric modalities are also examined, including face, periocular and iris. This timely volume is a mine of useful information for researchers, practitioners and students involved in image processing, computer vision, biometrics and security.
Reviews Refinements And New Ideas In Face Recognition
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Author : Peter Corcoran
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-07-27
Reviews Refinements And New Ideas In Face Recognition written by Peter Corcoran and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-27 with Computers categories.
As a baby one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section on Statistical Face Models and Classifiers presents reviews and refinements of some well-known statistical models. The next section presents two articles exploring the use of Infrared imaging techniques and is followed by few articles devoted to refinements of classical methods. New approaches to improve the robustness of face analysis techniques are followed by two articles dealing with real-time challenges in video sequences. A final article explores human perceptual issues of face recognition.
Recent Advances In Face Recognition
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Author : Kresimir Delac
language : en
Publisher: IntechOpen
Release Date : 2008-12-01
Recent Advances In Face Recognition written by Kresimir Delac and has been published by IntechOpen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-01 with Computers categories.
The main idea and the driver of further research in the area of face recognition are security applications and human-computer interaction. Face recognition represents an intuitive and non-intrusive method of recognizing people and this is why it became one of three identification methods used in e-passports and a biometric of choice for many other security applications. This goal of this book is to provide the reader with the most up to date research performed in automatic face recognition. The chapters presented use innovative approaches to deal with a wide variety of unsolved issues.
Reviews Refinements And New Ideas In Face Recognition
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Author : Peter Corcoran
language : en
Publisher: IntechOpen
Release Date : 2011-07-27
Reviews Refinements And New Ideas In Face Recognition written by Peter Corcoran and has been published by IntechOpen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-27 with Computers categories.
As a baby one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section on Statistical Face Models and Classifiers presents reviews and refinements of some well-known statistical models. The next section presents two articles exploring the use of Infrared imaging techniques and is followed by few articles devoted to refinements of classical methods. New approaches to improve the robustness of face analysis techniques are followed by two articles dealing with real-time challenges in video sequences. A final article explores human perceptual issues of face recognition.
Beyond Recognition
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Author : Le Minh-Ha
language : en
Publisher: Linköping University Electronic Press
Release Date : 2024-05-06
Beyond Recognition written by Le Minh-Ha and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-06 with categories.
This thesis addresses the need to balance the use of facial recognition systems with the need to protect personal privacy in machine learning and biometric identification. As advances in deep learning accelerate their evolution, facial recognition systems enhance security capabilities, but also risk invading personal privacy. Our research identifies and addresses critical vulnerabilities inherent in facial recognition systems, and proposes innovative privacy-enhancing technologies that anonymize facial data while maintaining its utility for legitimate applications. Our investigation centers on the development of methodologies and frameworks that achieve k-anonymity in facial datasets; leverage identity disentanglement to facilitate anonymization; exploit the vulnerabilities of facial recognition systems to underscore their limitations; and implement practical defenses against unauthorized recognition systems. We introduce novel contributions such as AnonFACES, StyleID, IdDecoder, StyleAdv, and DiffPrivate, each designed to protect facial privacy through advanced adversarial machine learning techniques and generative models. These solutions not only demonstrate the feasibility of protecting facial privacy in an increasingly surveilled world, but also highlight the ongoing need for robust countermeasures against the ever-evolving capabilities of facial recognition technology. Continuous innovation in privacy-enhancing technologies is required to safeguard individuals from the pervasive reach of digital surveillance and protect their fundamental right to privacy. By providing open-source, publicly available tools, and frameworks, this thesis contributes to the collective effort to ensure that advancements in facial recognition serve the public good without compromising individual rights. Our multi-disciplinary approach bridges the gap between biometric systems, adversarial machine learning, and generative modeling to pave the way for future research in the domain and support AI innovation where technological advancement and privacy are balanced.
