This book moves beyond the basics of "pushing the buttons"; explaining the most efficient and effective ways of using Xpress Pro to tell the story. Readers develop a working knowledge of the application with lessons and tutorials that cover every essential method and technique. An excellent resource for students and professional editors new to Xpress Pro, this book and DVD combo provides valuable hands-on practice with an extended example that demonstrates the edit of an entire sequence. Project media and plug-ins are provided on the companion DVD.
This book moves beyond the basics of 'pushing the buttons, ' explaining the most efficient and effective ways of using Xpress Pro to tell the story.

A timely and authoritative guide to the state of the art of wave scattering

Scattering of Electromagnetic Waves offers in three volumes a complete and up-to-date treatment of wave scattering by random discrete scatterers and rough surfaces. Written by leading scientists who have made important contributions to wave scattering over three decades, this new work explains the principles, methods, and applications of this rapidly expanding, interdisciplinary field. It covers both introductory and advanced material and provides students and researchers in remote sensing as well as imaging, optics, and electromagnetic theory with a one-stop reference to a wealth of current research results. Plus, Scattering of Electromagnetic Waves contains detailed discussions of both analytical and numerical methods, including cutting-edge techniques for the recovery of earth/land parametric information.

The three volumes are entitled respectively Theories and Applications, Numerical Simulation, and Advanced Topics. In the third volume, Advanced Topics, Leung Tsang (University of Washington) and Jin Au Kong (MIT), cover:

• Two-dimensional random rough surface scattering
• Kirchhoff and related methods for rough surface scattering
• Analytic theory of volume scattering based on cascading of layers
• Analytic wave theory for medium with permittivity fluctuations
• Multiple scattering theory for discrete scatterers
• Quasicrystalline approximation in dense media scattering
• Dense media scattering
• Backscattering enhancement

This book reports on the theoretical foundations, fundamental applications and latest advances in various aspects of connected services for health information systems. The twelve chapters highlight state-of-the-art approaches, methodologies and systems for the design, development, deployment and innovative use of multisensory systems and tools for health management in smart city ecosystems. They exploit technologies like deep learning, artificial intelligence, augmented and virtual reality, cyber physical systems and sensor networks. Presenting the latest developments, identifying remaining challenges, and outlining future research directions for sensing, computing, communications and security aspects of connected health systems, the book will mainly appeal to academic and industrial researchers in the areas of health information systems, smart cities, and augmented reality.

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.

This two-volume set of LNCS 12509 and 12510 constitutes the refereed proceedings of the 15th International Symposium on Visual Computing, ISVC 2020, which was supposed to be held in San Diego, CA, USA in October 2020, took place virtually instead due to the COVID-19 pandemic. The 114 full and 4 short papers presented in these volumes were carefully reviewed and selected from 175 submissions. The papers are organized into the following topical sections: Part I: deep learning; segmentation; visualization; video analysis and event recognition; ST: computational bioimaging; applications; biometrics; motion and tracking; computer graphics; virtual reality; and ST: computer vision advances in geo-spatial applications and remote sensing Part II: object recognition/detection/categorization; 3D reconstruction; medical image analysis; vision for robotics; statistical pattern recognition; posters

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

This book presents non-linear image enhancement approaches to mammograms as a robust computer-aided analysis solution for the early detection of breast cancer, and provides a compendium of non-linear mammogram enhancement approaches: from the fundamentals to research challenges, practical implementations, validation, and advances in applications. The book includes a comprehensive discussion on breast cancer, mammography, breast anomalies, and computer-aided analysis of mammograms. It also addresses fundamental concepts of mammogram enhancement and associated challenges, and features a detailed review of various state-of-the-art approaches to the enhancement of mammographic images and emerging research gaps. Given its scope, the book offers a valuable asset for radiologists and medical experts (oncologists), as mammogram visualization can enhance the precision of their diagnostic analyses; and for researchers and engineers, as the analysis of non-linear filters is one of the most challenging research domains in image processing.

Journalism Design is about the future of journalism. As technologies increasingly, and continually, reshape the way we interact with information, with each other and with our environment, journalists need new ways to tell stories. Journalists often see technology as something that improves what they are doing or that makes it more convenient. However, the growing might of technology companies has put journalism and news organisations in a difficult position: readers and revenues have moved, and platforms exert increasing control over story design. Skye Doherty argues that, rather than adapting journalism to new technologies, journalists should be creating the technologies themselves and those technologies should be designed for core values such as the public interest. Drawing from theories and practices of interaction design, this book demonstrates how journalists can use their expertise to imagine new ways of doing journalism. The design and development of the NewsCube, a three-dimensional storytelling tool, is detailed, as well as how interaction design can be used to imagine new forms of journalism. The book concludes by calling for closer ties between researchers and working journalists and suggests that journalism has a hybrid future - in newsrooms, communities, design studios and tech companies.

The book reports on cutting-edge Artificial Intelligence (AI) theories and methods aimed at the control and coordination of agents acting and moving in a dynamic environment. It covers a wide range of topics relating to: autonomous navigation, localization and mapping; mobile and social robots; multiagent systems; human-robot interaction; perception systems; and deep-learning techniques applied to the robotics. Based on the 21st edition of the International Workshop of Physical Agents (WAF 2020), held virtually on November 19-20, 2020, from Alcala de Henares, Madrid, Spain, this book offers a snapshot of the state-of-the-art in the field of physical agents, with a special emphasis on novel AI techniques in perception, navigation and human robot interaction for autonomous systems.

This book introduces readers to the fundamentals of creating presentation graphics using R, based on 111 detailed and complete scripts. It shows how bar and column charts, population pyramids, Lorenz curves, box plots, scatter plots, time series, radial polygons, Gantt charts, heat maps, bump charts, mosaic and balloon charts, and a series of different thematic map types can be created using R's Base Graphics System. Every example uses real data and includes step-by-step explanations of the figures and their programming. This second edition contains additional examples for cartograms, chord-diagrams and networks, and interactive visualizations with Javascript. The open source software R is an established standard and a powerful tool for various visualizing applications, integrating nearly all technologies relevant for data visualization. The basic software, enhanced by more than 14000 extension packs currently freely available, is intensively used by organizations including Google, Facebook and the CIA. The book serves as a comprehensive reference guide to a broad variety of applications in various fields. This book is intended for all kinds of R users, ranging from experts, for whom especially the example codes are particularly useful, to beginners, who will find the finished graphics most helpful in learning what R can actually deliver.

The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as 'hand-crafted features.' It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images. Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book's main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.

This book constitutes the thoroughly refereed papers of the Second International Conference on Applied Informatics, ICAI 2020, held in Ota, Nigeria, in October 2020. The 35 full papers were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections on artificial intelligence; business process management; cloud computing; data analysis; decision systems; health care information systems; human-computer interaction; image processing; learning management systems; software design engineering.

This book discusses the computational geometry, topology and physics of digital images and video frame sequences. This trio of computational approaches encompasses the study of shape complexes, optical vortex nerves and proximities embedded in triangulated video frames and single images, while computational geometry focuses on the geometric structures that infuse triangulated visual scenes. The book first addresses the topology of cellular complexes to provide a basis for an introductory study of the computational topology of visual scenes, exploring the fabric, shapes and structures typically found in visual scenes. The book then examines the inherent geometry and topology of visual scenes, and the fine structure of light and light caustics of visual scenes, which bring into play catastrophe theory and the appearance of light caustic folds and cusps. Following on from this, the book introduces optical vortex nerves in triangulated digital images. In this context, computational physics is synonymous with the study of the fine structure of light choreographed in video frames. This choreography appears as a sequence of snapshots of light reflected and refracted from surface shapes, providing a solid foundation for detecting, analyzing and classifying visual scene shapes.

This book constitutes the extended abstracts of the posters presented during the 22nd International Conference on Human-Computer Interaction, HCII 2020, which was held in July 2020. The conference was planned to take place in Copenhagen, Denmark, but had to change to a virtual conference mode due to the COVID-19 pandemic. From a total of 6326 submissions, a total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings before the conference took place. In addition, a total of 333 papers and 144 posters are included in the volumes of the proceedings published after the conference as "Late Breaking Work" (papers and posters). These contributions address the latest research and development efforts in the field and highlight the human aspects of design and use of computing systems. The 82 papers presented in this volume are organized in topical sections as follows: design for all and sssisitive technologies; virtual, augmented and mixed reality; learning; HCI, culture and art; health and wellbeing applications; HCI in mobility, automotive and aviation.

This book is about composition and its application in animation, illustration, games and film. It covers all various aspects of design and explains in detail the use of the specific aspect and provides examples of its impact. Focus is on the ability of each aspect to tell a story and how it affects story. Additionally case studies are included that explain the successful use of those aspects in film and animation. The book is geared to students and professionals, however tries to be as simple as possible in the presentation of each aspect, but also complex in its case studies. The book's goal is to see composition as a technical part of image and film and as an artistic tool. Key Features Teaches the complexity of composition in image making. Closes the gap between praxis and theory in animation. Explains why certain images have a high quality and how to use the "whoy" in one's personal artistic work on a daily basis. Key term definitions found throughout the chapters. Case studies and video clips help the reader understand the process as they progress through the book.

This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXI International Conference on Neuroinformatics, held on October 7-11, 2019, in Dolgoprudny, a town in Moscow region, Russia.

This book introduces the principle of carrying out a medium-term load forecast (MTLF) at power system level, based on the Big Data concept and Convolutionary Neural Network (CNNs). It also presents further research directions in the field of Deep Learning techniques and Big Data, as well as how these two concepts are used in power engineering. Efficient processing and accuracy of Big Data in the load forecast in power engineering leads to a significant improvement in the consumption pattern of the client and, implicitly, a better consumer awareness. At the same time, new energy services and new lines of business can be developed. The book will be of interest to electrical engineers, power engineers, and energy services professionals.

Create assets for history-based games. This book covers the fundamental principles required to understand and create architectural visualizations of historical locations using digital tools. You will explore aspects of 3D design visualization and VR integration using industry-preferred software. Some of the most popular video games in recent years have historical settings (Age of Empires, Call of Duty, etc.). Creating these games requires creating historically accurate game assets. You will use Blender to create VR-ready assets by modeling and unwrapping them. And you will use Substance Painter to texture the assets that you create. You will also learn how to use the Quixel Megascans library to acquire and implement physically accurate materials in the scenes. Finally, you will import the assets into Unreal Engine 4 and recreate a VR integrated heritage that can be explored in real time. Using VR technology and game engines, you can digitally recreate historical settings for games. What You Will Learn Create high-quality, optimized models suitable for any 3D game engine Master the techniques of texturing assets using Substance Painter and Quixel Megascans Keep assets historically accurate Integrate assets with the game engine Create visualizations with Unreal Engine 4 Who Is This Book For Game developers with some experience who are eager to get into VR-based games

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

Adaptive filtering is a classical branch of digital signal processing (DSP). Industrial interest in adaptive filtering grows continuously with the increase in computer performance that allows ever more conplex algorithms to be run in real-time. Change detection is a type of adaptive filtering for non-stationary signals and is also the basic tool in fault detection and diagnosis.

Often considered as separate subjects Adaptive Filtering and Change Detection bridges a gap in the literature with a unified treatment of these areas, emphasizing that change detection is a natural extension of adaptive filters, and adaptive filters are the basic building blocks in all change detectors.
By providing a timely and innovative resource, applied engineers, researchers and postgraduate students studying DSP will all find this an indispensable and enlightening read!

• Presents a comprehensive and complete treatment of adapative filtering

• Provides a unifying framework for the theory of change detection based on a filtering approach

• Combines mathematical tools (algebra, calculus, statistics) and applications areas (airborne, automotive, communication systems, standard signal processing and automatic control applications)

• Features extensive examples and case studies which can be reproduced and investigated in an accompanying Matlab demo toolbox.

This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way. Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines.

This book gathers high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2020) [formerly ICCASP]. A flagship conference on engineering and emerging next-generation technologies, it was jointly organized by Dr. Babasaheb Ambedkar Technological University and MGMs College of Engineering, Nanded, India on 9-11 January 2020. Focusing on applied computer vision and image processing, this proceedings volume includes papers on image processing, computer vision, pattern recognition, and DSP/DIP applications in healthcare systems.

This updated and revised edition of a classic work provides a summary of methods for numerical computation of high resolution conventional and scanning transmission electron microscope images. At the limits of resolution, image artifacts due to the instrument and the specimen interaction can complicate image interpretation. Image calculations can help the user to interpret and understand high resolution information in recorded electron micrographs. The book contains expanded sections on aberration correction, including a detailed discussion of higher order (multipole) aberrations and their effect on high resolution imaging, new imaging modes such as ABF (annular bright field), and the latest developments in parallel processing using GPUs (graphic processing units), as well as updated references. Beginning and experienced users at the advanced undergraduate or graduate level will find the book to be a unique and essential guide to the theory and methods of computation in electron microscopy.