This book revises and expands upon the prior edition of Multi-Modal Face Presentation Attack Detection. The authors begin with fundamental and foundational information on face spoofing attack detection, explaining why the computer vision community has intensively studied it for the last decade. The authors also discuss the reasons that cause face anti-spoofing to be essential for preventing security breaches in face recognition systems. In addition, the book describes the factors that make it difficult to design effective methods of face presentation attack detection challenges. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face anti-spoofing that would lead to progress in the field. Additional analysis, new methodologies, and a more comprehensive survey of solutions are included in this new edition.
For the last ten years, face biometric research has been intensively studied by the computer vision community. Face recognition systems have been used in mobile, banking, and surveillance systems. For face recognition systems, face spoofing attack detection is a crucial stage that could cause severe security issues in government sectors. Although effective methods for face presentation attack detection have been proposed so far, the problem is still unsolved due to the difficulty in the design of features and methods that can work for new spoofing attacks. In addition, existing datasets for studying the problem are relatively small which hinders the progress in this relevant domain. In order to attract researchers to this important field and push the boundaries of the state of the art on face anti-spoofing detection, we organized the Face Spoofing Attack Workshop and Competition at CVPR 2019, an event part of the ChaLearn Looking at People Series. As part of this event, we released the largest multi-modal face anti-spoofing dataset so far, the CASIA-SURF benchmark. The workshop reunited many researchers from around the world and the challenge attracted more than 300 teams. Some of the novel methodologies proposed in the context of the challenge achieved state-of-the-art performance. In this manuscript, we provide a comprehensive review on face anti-spoofing techniques presented in this joint event and point out directions for future research on the face anti-spoofing field.
A comprehensive work in finite-value systems that covers the latest achievements using the semi-tensor product method, on various kinds of finite-value systems. These results occupy the highest position in the analysis and control of this field. It not only covers all aspects of research in finite-value systems, but also presents the mathematical derivation for each conclusion in depth. The book contains examples to provide a better understanding of the practical applications of finite-value systems. It will serve as a textbook for graduate students of Cybernetics, Mathematical, and Biology, and a reference for readers interested in the theory of finite-value systems.
This book provides a general survey of Geocryology, which is the study of frozen ground called permafrost. Frozen ground is the product of cold climates as well as a variety of environmental factors. Its major characteristic is the accumulation of large quantities of ice which may exceed 90% by volume. Soil water changing to ice results in ground heaving, while thawing of this ice produces ground subsidence often accompanied by soil flowage. Permafrost is very susceptible to changes in weather and climate as well as to changes in the microenvironment. Cold weather produces contraction of the ground, resulting in cracking of the soil as well as breakup of concrete, rock, etc. Thus permafrost regions have unique landforms and processes not found in warmer lands. The book is divided into three parts. Part 1 provides an introduction to the characteristics of permafrost. Four chapters deal with its definition and characteristics, the unique processes operating there, the factors affecting it, and its general distribution. Part 2 consists of seven chapters describing the characteristic landforms unique to these areas and the processes involved in their formation. Part 3 discusses the special problems encountered by engineers in construction projects including settlements, roads and railways, the oil and gas industry, mining, and the agricultural and forest industries. The three authors represent three countries and three language groups, and together have over 120 years of experience of working in permafrost areas throughout the world. The book contains over 300 illustrations and photographs, and includes an extensive bibliography in order to introduce the interested reader to the large current literature. Finalist of the 2019 PROSE Awards.
The book highlights the current practices and future trends in structural characterization of impurities and degradants. It begins with an overview of mass spectrometry techniques as related to the analysis of impurities and degradants, followed by studies involving characterization of process related impurities (including potential genotoxic impurities), and excipient related impurities in formulated products. Both general practitioners in pharmaceutical research and specialists in analytical chemistry field will benefit from this book that will detail step-by-step approaches and new strategies to solve challenging problems related to pharmaceutical research.
This SpringerBrief investigates advanced sensing techniques to detect and estimate the primary receiver for cognitive radio systems. Along with a comprehensive overview of existing spectrum sensing techniques, this brief focuses on the design of new signal processing techniques, including the region-based sensing, jamming-based probing, and relay-based probing. The proposed sensing techniques aim to detect the nearby primary receiver and estimate the cross-channel gain between the cognitive transmitter and primary receiver. The performance of the proposed algorithms is evaluated by simulations in terms of several performance parameters, including detection probability, interference probability, and estimation error. The results show that the proposed sensing techniques can effectively sense the primary receiver and improve the cognitive transmission throughput. Researchers and postgraduate students in electrical engineering will find this an exceptional resource.
For the last ten years, face biometric research has been intensively studied by the computer vision community. Face recognition systems have been used in mobile, banking, and surveillance systems. For face recognition systems, face spoofing attack detection is a crucial stage that could cause severe security issues in government sectors. Although effective methods for face presentation attack detection have been proposed so far, the problem is still unsolved due to the difficulty in the design of features and methods that can work for new spoofing attacks. In addition, existing datasets for studying the problem are relatively small which hinders the progress in this relevant domain. In order to attract researchers to this important field and push the boundaries of the state of the art on face anti-spoofing detection, we organized the Face Spoofing Attack Workshop and Competition at CVPR 2019, an event part of the ChaLearn Looking at People Series. As part of this event, we released the largest multi-modal face anti-spoofing dataset so far, the CASIA-SURF benchmark. The workshop reunited many researchers from around the world and the challenge attracted more than 300 teams. Some of the novel methodologies proposed in the context of the challenge achieved state-of-the-art performance. In this manuscript, we provide a comprehensive review on face anti-spoofing techniques presented in this joint event and point out directions for future research on the face anti-spoofing field.
For the last ten years, face biometric research has been intensively studied by the computer vision community. Face recognition systems have been used in mobile, banking, and surveillance systems. For face recognition systems, face spoofing attack detection is a crucial stage that could cause severe security issues in government sectors. Although effective methods for face presentation attack detection have been proposed so far, the problem is still unsolved due to the difficulty in the design of features and methods that can work for new spoofing attacks. In addition, existing datasets for studying the problem are relatively small which hinders the progress in this relevant domain. In order to attract researchers to this important field and push the boundaries of the state of the art on face anti-spoofing detection, we organized the Face Spoofing Attack Workshop and Competition at CVPR 2019, an event part of the ChaLearn Looking at People Series. As part of this event, we released the largest multi-modal face anti-spoofing dataset so far, the CASIA-SURF benchmark. The workshop reunited many researchers from around the world and the challenge attracted more than 300 teams. Some of the novel methodologies proposed in the context of the challenge achieved state-of-the-art performance. In this manuscript, we provide a comprehensive review on face anti-spoofing techniques presented in this joint event and point out directions for future research on the face anti-spoofing field.
For the last ten years, face biometric research has been intensively studied by the computer vision community. Face recognition systems have been used in mobile, banking, and surveillance systems. For face recognition systems, face spoofing attack detection is a crucial stage that could cause severe security issues in government sectors. Although effective methods for face presentation attack detection have been proposed so far, the problem is still unsolved due to the difficulty in the design of features and methods that can work for new spoofing attacks. In addition, existing datasets for studying the problem are relatively small which hinders the progress in this relevant domain. In order to attract researchers to this important field and push the boundaries of the state of the art on face anti-spoofing detection, we organized the Face Spoofing Attack Workshop and Competition at CVPR 2019, an event part of the ChaLearn Looking at People Series. As part of this event, we released the largest multi-modal face anti-spoofing dataset so far, the CASIA-SURF benchmark. The workshop reunited many researchers from around the world and the challenge attracted more than 300 teams. Some of the novel methodologies proposed in the context of the challenge achieved state-of-the-art performance. In this manuscript, we provide a comprehensive review on face anti-spoofing techniques presented in this joint event and point out directions for future research on the face anti-spoofing field.
This book revises and expands upon the prior edition of Multi-Modal Face Presentation Attack Detection. The authors begin with fundamental and foundational information on face spoofing attack detection, explaining why the computer vision community has intensively studied it for the last decade. The authors also discuss the reasons that cause face anti-spoofing to be essential for preventing security breaches in face recognition systems. In addition, the book describes the factors that make it difficult to design effective methods of face presentation attack detection challenges. The book presents a thorough review and evaluation of current techniques and identifies those that have achieved the highest level of performance in a series of ChaLearn face anti-spoofing challenges at CVPR and ICCV. The authors also highlight directions for future research in face anti-spoofing that would lead to progress in the field. Additional analysis, new methodologies, and a more comprehensive survey of solutions are included in this new edition.
A comprehensive work in finite-value systems that covers the latest achievements using the semi-tensor product method, on various kinds of finite-value systems. These results occupy the highest position in the analysis and control of this field. It not only covers all aspects of research in finite-value systems, but also presents the mathematical derivation for each conclusion in depth. The book contains examples to provide a better understanding of the practical applications of finite-value systems. It will serve as a textbook for graduate students of Cybernetics, Mathematical, and Biology, and a reference for readers interested in the theory of finite-value systems.
A comprehensive work in finite-value systems that covers the latest achievements using the semi-tensor product method, on various kinds of finite-value systems. The book contains examples to provide a better understanding of the practical applications of finite-value systems.
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