"This book provides related theoretical background to understand the overall configuration and challenging problem of automated face analysis systems"--Provided by publisher.

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.

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 book reports on research and developments in human–technology interaction. A special emphasis is given to human–computer interaction and its implementation for a wide range of purposes such as health care, aerospace, telecommunication, and education, among others. The human aspects are analyzed in detail. Timely studies on human-centered design, wearable technologies, social and affective computing, augmented, virtual and mixed reality simulation, human rehabilitation, and biomechanics represent the core of the book. Emerging technology applications in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically grounded, but also professionally oriented snapshot of the current state of the field. The book gathers contributions presented at the 5th International Conference on Human Interaction and Emerging Technologies (IHIET 2021, August 27–29, 2021) and the 6th International Conference on Human Interaction and Emerging Technologies: Future Systems (IHIET-FS 2021, October 28–30, 2021), held virtually from France. It offers a timely survey and a practice-oriented reference guide to researchers and professionals dealing with design, systems engineering, and management of the next-generation technology and service systems.

This book emphasizes recent advances in the creation of biometric identification systems for various applications in the field of human activity. The book displays the problems that arise in modern systems of biometric identification, as well as the level of development and prospects for the introduction of biometric technologies. The authors classify biometric technologies into two groups, distinguished according to the type of biometric characteristics used. The first group uses static biometric parameters: fingerprints, hand geometry, retina pattern, vein pattern on the finger, etc. The second group uses dynamic parameters for identification: the dynamics of the reproduction of a signature or a handwritten keyword, voice, gait, dynamics of work on the keyboard, etc. The directions of building information systems that use automatic personality identification based on the analysis of unique biometric characteristics of a person are discussed. The book is intended for professionals working and conducting research in the field of intelligent information processing, information security, and robotics and in the field of real-time identification systems. The book contains examples and problems/solutions throughout.

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.

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.