In recent years, falsification and digital modification of video clips, images, as well as textual contents have become widespread and numerous, especially when deepfake technologies are adopted in many sources. Due to adopted deepfake techniques, a lot of content currently cannot be recognized from its original sources. As a result, the field of study previously devoted to general multimedia forensics has been revived. The Handbook of Research on Advanced Practical Approaches to Deepfake Detection and Applications discusses the recent techniques and applications of illustration, generation, and detection of deepfake content in multimedia. It introduces the techniques and gives an overview of deepfake applications, types of deepfakes, the algorithms and applications used in deepfakes, recent challenges and problems, and practical applications to identify, generate, and detect deepfakes. Covering topics such as anomaly detection, intrusion detection, and security enhancement, this major reference work is a comprehensive resource for cyber security specialists, government officials, law enforcement, business leaders, students and faculty of higher education, librarians, researchers, and academicians.

Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention.

Change Detection and Image Time Series Analysis 2 presents supervised machine-learning-based methods for temporal evolution analysis by using image time series associated with Earth observation data. Chapter 1 addresses the fusion of multisensor, multiresolution and multitemporal data. It proposes two supervised solutions that are based on a Markov random field: the first relies on a quad-tree and the second is specifically designed to deal with multimission, multifrequency and multiresolution time series. Chapter 2 provides an overview of pixel based methods for time series classification, from the earliest shallow learning methods to the most recent deep-learning-based approaches. Chapter 3 focuses on very high spatial resolution data time series and on the use of semantic information for modeling spatio-temporal evolution patterns. Chapter 4 centers on the challenges of dense time series analysis, including pre processing aspects and a taxonomy of existing methodologies. Finally, since the evaluation of a learning system can be subject to multiple considerations, Chapters 5 and 6 offer extensive evaluations of the methodologies and learning frameworks used to produce change maps, in the context of multiclass and/or multilabel change classification issues.

Usability Testing for Survey Research provides researchers with a guide to the tools necessary to evaluate, test, and modify surveys in an iterative method during the survey pretesting process. It includes examples that apply usability to any type of survey during any stage of development, along with tactics on how to tailor usability testing to meet budget and scheduling constraints. The book's authors distill their experience to provide tips on how usability testing can be applied to paper surveys, mixed-mode surveys, interviewer-administered tools, and additional products. Readers will gain an understanding of usability and usability testing and why it is needed for survey research, along with guidance on how to design and conduct usability tests, analyze and report findings, ideas for how to tailor usability testing to meet budget and schedule constraints, and new knowledge on how to apply usability testing to other survey-related products, such as project websites and interviewer administered tools.

Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.

This book describes the signal, image and video processing methods and techniques for fire detection and provides a thorough and practical overview of this important subject, as a number of new methods are emerging. This book will serve as a reference for signal processing and computer vision, focusing on fire detection and methods for volume sensors. Applications covered in this book can easily be adapted to other domains, such as multi-modal object recognition in other safety and security problems, with scientific importance for fire detection, as well as video surveillance. Coverage includes: Camera Based Techniques Multi-modal/Multi-sensor fire analysis Pyro-electric Infrared Sensors for Flame Detection Large scale fire experiments Wildfire detection from moving aerial platforms

Image data has portrayed immense potential as a foundation of information for numerous applications. Recent trends in multimedia computing have witnessed a rapid growth in digital image collections, resulting in a need for increased image data management. Feature Dimension Reduction for Content-Based Image Identification is a pivotal reference source that explores the contemporary trends and techniques of content-based image recognition. Including research covering topics such as feature extraction, fusion techniques, and image segmentation, this book explores different theories to facilitate timely identification of image data and managing, archiving, maintaining, and extracting information. This book is ideally designed for engineers, IT specialists, researchers, academicians, and graduate-level students seeking interdisciplinary research on image processing and analysis.

Interfaces within computers, computing, and programming are consistently evolving and continue to be relevant to computer science as it progresses. Advancements in human-computer interactions, their aesthetic appeal, ease of use, and learnability are made possible due to the creation of user interfaces and result in further growth in science, aesthetics, and practical applications. Interface Support for Creativity, Productivity, and Expression in Computer Graphics is a collection of innovative research on usability, the apps humans use, and their sensory environment. While highlighting topics such as image datasets, augmented reality, and visual storytelling, this book is ideally designed for researchers, academicians, graphic designers, programmers, software developers, educators, multimedia specialists, and students seeking current research on uniting digital content with the physicality of the device through applications, thus addressing sensory perception.

Digital image processing is a field that is constantly improving. Gaining high-level understanding from digital images is a key requirement for computing. One aspect of study that is assisting with this advancement is fractal theory. This new science has gained momentum and popularity as it has become a key topic of research in the area of image analysis. Examining Fractal Image Processing and Analysis is an essential reference source that discusses fractal theory applications and analysis, including box-counting analysis, multi-fractal analysis, 3D fractal analysis, and chaos theory, as well as recent trends in other soft computing techniques. Featuring research on topics such as image compression, pattern matching, and artificial neural networks, this book is ideally designed for system engineers, computer engineers, professionals, academicians, researchers, and students seeking coverage on problem-oriented processing techniques and imaging technologies.

Image and Video Processing is an active area of research due to its potential applications for solving real-world problems. Integrating computational intelligence to analyze and interpret information from image and video technologies is an essential step to processing and applying multimedia data. Emerging Technologies in Intelligent Applications for Image and Video Processing presents the most current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. Featuring insight from researchers from around the world, this publication is designed for use by engineers, IT specialists, researchers, and graduate level students.

Security video surveillance systems, such as homeland security and national defence, rely on specific mathematical algorithms in order to run effectively. It is essential for these parameters to be understood in order to design and create a successful system. Video Surveillance Techniques and Technologies presents empirical research and acquired experience on the original solutions and mathematical algorithms for motion detection and object identification problems. Emphasising a wide variety of applications of security systems, this book is an essential tool for graduate students and professionals in the field of signal and image processing applied in static/moving object detection, tracking, and identification.

Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.

In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification and performance evaluation and prediction.

Conventional topographic databases, obtained by capture on aerial or spatial images provide a simplified 3D modeling of our urban environment, answering the needs of numerous applications (development, risk prevention, mobility management, etc.). However, when we have to represent and analyze more complex sites (monuments, civil engineering works, archeological sites, etc.), these models no longer suffice and other acquisition and processing means have to be implemented. This book focuses on the study of adapted lifting means for notable buildings . The methods tackled in this book cover lasergrammetry and the current techniques of dense correlation based on images using conventional photogrammetry.

With the advancement of technology in the modern world, the constant influx of data, information, and computing can become droning and one-dimensional. Re-examining these methods through a different approach helps highlight broader perspectives and further understanding. Applying abstract and holistic methods, such as nature and visualization, to computing technologies is a developing area of study but has yet to be empirically researched. Graphical Thinking for Science and Technology Through Knowledge Visualization provides emerging research exploring the theoretical and practical aspects of implementing visuals and images within data and information. The text contains projects, examples of students' solutions, and invites the reader to apply graphical thinking. Featuring coverage on a broad range of topics such as nanoscale structures, computer graphics, and data visualization, this book is ideally designed for software engineers, instructional designers, researchers, scientists, artists, marketers, media professionals, and students seeking current research on applying artistic solutions within information and computing.

This book takes a hemispheric approach to contemporary urban intervention, examining urban ecologies, communication technologies, and cultural practices in the twenty-first century. It argues that governmental and social regimes of control and forms of political resistance converge in speculation on disaster and that this convergence has formed a vision of urban environments in the Americas in which forms of play and imaginations of catastrophe intersect in the vertical field. Schifani explores a diverse range of resistant urban interventions, imagining the city as on the verge of or enmeshed in catastrophe. She also presents a model of ecocriticism that addresses aesthetic practices and forms of play in the urban environment. Tracing the historical roots of such tactics as well as mapping their hopes for the future will help the reader to locate the impacts of climate change not only on the physical space of the city, but also on the epistemological and aesthetic strategies that cities can help to engender. This book will be of great interest to students and scholars of Urban Studies, Media Studies, American Studies, Global Studies, and the broad and interdisciplinary field of Environmental Humanities.

Congruences are ubiquitous in computer science, engineering, mathematics, and related areas. Developing techniques for finding (the number of) solutions of congruences is an important problem. But there are many scenarios in which we are interested in only a subset of the solutions; in other words, there are some restrictions. What do we know about these restricted congruences, their solutions, and applications? This book introduces the tools that are needed when working on restricted congruences and then systematically studies a variety of restricted congruences. Restricted Congruences in Computing defines several types of restricted congruence, obtains explicit formulae for the number of their solutions using a wide range of tools and techniques, and discusses their applications in cryptography, information security, information theory, coding theory, string theory, quantum field theory, parallel computing, artificial intelligence, computational biology, discrete mathematics, number theory, and more. This is the first book devoted to restricted congruences and their applications. It will be of interest to graduate students and researchers across computer science, electrical engineering, and mathematics.

A compilation of key chapters from the top MK computer animation books available today - in the areas of motion capture, facial features, solid spaces, fluids, gases, biology, point-based graphics, and Maya. The chapters provide CG Animators with an excellent sampling of essential techniques that every 3D artist needs to create stunning and versatile images. Animators will be able to master myriad modeling, rendering, and texturing procedures with advice from MK's best and brightest authors.

Divided into five parts (Introduction to Computer Animation and Technical Background, Motion Capture Techniques, Animating Substances, Alternate Methods, and Animating with MEL for MAYA), each one focusing on specific substances, tools, topics, and languages, this is a MUST-HAVE book for artists interested in proficiency with the top technology available today Whether you're a programmer developing new animation functionality or an animator trying to get the most out of your current animation software, Computer Animation Complete: will help you work more efficiently and achieve better results. For programmers, this book provides a solid theoretical orientation and extensive practical instruction information you can put to work in any development or customization project. For animators, it provides crystal-clear guidance on determining which of your concepts can be realized using commercially available products, which demand custom programming, and what development strategies are likely to bring you the greatest success.
Expert instruction from a variety of pace-setting computer graphics researchers.Provides in-depth coverage of established and emerging animation algorithms.For readers who lack a strong scientific background, introduces the necessary concepts from mathematics, biology, and physics.A variety of individual languages and substances are addressed, but addressed separately - enhancing your grasp of the field as a whole while providing you with the ability to identify and implement solutions by category.

This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes.

After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLAB codes and figures are included. The final chapter considers advanced concepts and trends in ISAR imaging.