This book examines how face recognition technology is affecting privacy and confidentiality in an era of enhanced surveillance. Further, it offers a new approach to the complex issues of privacy and confidentiality, by drawing on Joseph K in Kafka’s disturbing novel The Trial, and on Isaiah Berlin’s notion of liberty and freedom. Taking into consideration rights and wrongs, protection from harm associated with compulsory visibility, and the need for effective data protection law, the author promotes ethical practices by reinterpreting privacy as a property right. To protect this right, the author advocates the licensing of personal identifiable images where appropriate. The book reviews American, UK and European case law concerning privacy and confidentiality, the effect each case has had on the developing jurisprudence, and the ethical issues involved. As such, it offers a valuable resource for students of ethico-legal fields, professionals specialising in image rights law, policy-makers, and liberty advocates and activists.
Face recognition technologies (FRTs) have many practical security-related purposes, but advocacy groups and individuals have expressed apprehensions about their use. This report highlights the high-level privacy and bias implications of FRT systems. The authors propose a heuristic with two dimensions -- consent status and comparison type -- to help determine a proposed FRT's level of privacy and accuracy. They also identify privacy and bias concerns.
Since the 1960s, a significant effort has been underway to program computers to “see” the human face—to develop automated systems for identifying faces and distinguishing them from one another—commonly known as Facial Recognition Technology. While computer scientists are developing FRT in order to design more intelligent and interactive machines, businesses and states agencies view the technology as uniquely suited for “smart” surveillance—systems that automate the labor of monitoring in order to increase their efficacy and spread their reach. Tracking this technological pursuit, Our Biometric Future identifies FRT as a prime example of the failed technocratic approach to governance, where new technologies are pursued as shortsighted solutions to complex social problems. Culling news stories, press releases, policy statements, PR kits and other materials, Kelly Gates provides evidence that, instead of providing more security for more people, the pursuit of FRT is being driven by the priorities of corporations, law enforcement and state security agencies, all convinced of the technology’s necessity and unhindered by its complicated and potentially destructive social consequences. By focusing on the politics of developing and deploying these technologies, Our Biometric Future argues not for the inevitability of a particular technological future, but for its profound contingency and contestability.
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.
Automated facial recognition algorithms are increasingly intervening in society. This book offers a unique analysis of these algorithms from a critical visual culture studies perspective. The first part of this study examines the example of an early facial recognition algorithm called »eigenface« and traces a history of the merging of statistics and vision. The second part addresses contemporary artistic engagements with facial recognition technology in the work of Thomas Ruff, Zach Blas, and Trevor Paglen. This book argues that we must take a closer look at the technology of automated facial recognition and claims that its forms of representation are embedded with visual politics. Even more significantly, this technology is redefining what it means to see and be seen in the contemporary world.
"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.
The NATO Advanced Study Institute (ASI) on Face Recognition: From Theory to Applications took place in Stirling, Scotland, UK, from June 23 through July 4, 1997. The meeting brought together 95 participants (including 18 invited lecturers) from 22 countries. The lecturers are leading researchers from academia, govemment, and industry from allover the world. The lecturers presented an encompassing view of face recognition, and identified trends for future developments and the means for implementing robust face recognition systems. The scientific programme consisted of invited lectures, three panels, and (oral and poster) presentations from students attending the AS!. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (i) human processing of face recognition and its relevance to forensic systems, (ii) face coding, (iii) connectionist methods and support vector machines (SVM), (iv) hybrid methods for face recognition, and (v) predictive learning and performance evaluation. The goals of the panels were to provide links among the lectures and to emphasis the themes of the meeting. The topics of the panels were: (i) How the human visual system processes faces, (ii) Issues in applying face recognition: data bases, evaluation and systems, and (iii) Classification issues involved in face recognition. The presentations made by students gave them an opportunity to receive feedback from the invited lecturers and suggestions for future work.
Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver's license issuance, law enforcement investigations, and physical access control.Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face de
Named a Notable Work of Nonfiction of 2020 by the Washington Post As heard on NPR's Fresh Air, We Have Been Harmonized, by award-winning correspondent Kai Strittmatter, offers a groundbreaking look, based on decades of research, at how China created the most terrifying surveillance state in history. China’s new drive for repression is being underpinned by unprecedented advances in technology: facial and voice recognition, GPS tracking, supercomputer databases, intercepted cell phone conversations, the monitoring of app use, and millions of high-resolution security cameras make it nearly impossible for a Chinese citizen to hide anything from authorities. Commercial transactions, including food deliveries and online purchases, are fed into vast databases, along with everything from biometric information to social media activities to methods of birth control. Cameras (so advanced that they can locate a single person within a stadium crowd of 60,000) scan for faces and walking patterns to track each individual’s movement. In some schools, children’s facial expressions are monitored to make sure they are paying attention at the right times. In a new Social Credit System, each citizen is given a score for good behavior; for those who rate poorly, punishments include being banned from flying or taking high-speed trains, exclusion from certain jobs, and preventing their children from attending better schools. And it gets worse: advanced surveillance has led to the imprisonment of more than a million Chinese citizens in western China alone, many held in draconian “reeducation” camps. This digital totalitarianism has been made possible not only with the help of Chinese private tech companies, but the complicity of Western governments and corporations eager to gain access to China’s huge market. And while governments debate trade wars and tariffs, the Chinese Communist Party and its local partners are aggressively stepping up their efforts to export their surveillance technology abroad—including to the United States. We Have Been Harmonized is a terrifying portrait of life under unprecedented government surveillance—and a dire warning about what could happen anywhere under the pretense of national security. “Terrifying. … A warning call." —The Sunday Times (UK), a “Best Book of the Year so Far”
Face recognition has been an active area of research in image processing and computer vision due to its extensive range of prospective applications relating to biometrics, information security, video surveillance, law enforcement, identity authentication, smart cards, and access control systems. Topics discussed in this compilation include two-dimensional principal component analysis algorithms for face recognition; principal component analysis (PCA) and artificial immune networks in face recognition; multi-class learning facial age estimation and forensic face recognition.
