This book provides a critical account of the impact of Twitter on journalism, exploring how the news media has adapted to and normalised the use of the platform in the industry. Offering a comprehensive understanding of Twitter uses for journalistic purposes, this book explores the platform's use as a 'global village', as an ambient news environment, and as a global marketplace. Drawing on two empirical case studies (United Kingdom and Greece), Dagoula examines academic conceptualisations of Twitter, journalists' self-perceptions, and uses of the platform by a variety of media outlets and journalists. Adopting an evolutionary approach known as punctuated equilibrium, which consists of three stages of disruption, adaption, and normalisation, the author reveals the costs and benefits of Twitter's impact on both the institutional values and practices of news journalism today. News Journalism and Twitter is an invaluable resource for researchers and students of digital journalism and media studies.

* Provides a comprehensive approach to Motion Design as Design Practice with specific areas of focus for a range of audiences. * Integrates professional examples, case studies, and interviews to validate its themes. * Written from ongoing and pragmatic experience in both education and professional practice.

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15-17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learning and signal processing for engineering problems.

Multimodal Video Characterization and Summarization is a valuable research tool for both professionals and academicians working in the video field. This book describes the methodology for using multimodal audio, image, and text technology to characterize video content. This new and groundbreaking science has led to many advances in video understanding, such as the development of a video summary. Applications and methodology for creating video summaries are described, as well as user-studies for evaluation and testing.

Analyses a variety of approaches to development and publishing, across a multitude of platforms and genres, to provide a new vision for the next twenty years of game development. Considers technical advances in adjacent markets and how they will impact the games industry over the next twenty years. Includes insightful interviews from leading game and entertainment industry figures.

At long last, film and video editors are using the same systems to edi t their projects, and Editing Digital Film is the guide to show them h ow to do it. This concise reference provides video and film editors fa miliar with the Avid, Media 100, and Final Cut Pro systems with crucia l information they will need to edit on all three of these systems. In addition to showing film editors and directors working on DV projects how to edit for this new format, this text also clarifies the NLE pro cess to those familiar with traditional film editing.

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications

Thisbookpresentsmaterialwhichismorealgorithmicallyorientedthanmost alternatives.Italsodealswithtopicsthatareatorbeyondthestateoftheart. Examples include practical and applicable wavelet and other multiresolution transform analysis. New areas are broached like the ridgelet and curvelet transforms. The reader will ?nd in this book an engineering approach to the interpretation of scienti?c data. Compared to the 1st Edition, various additions have been made throu- out, and the topics covered have been updated. The background or en- ronment of this book's topics include continuing interest in e-science and the virtual observatory, which are based on web based and increasingly web service based science and engineering. Additional colleagues whom we would like to acknowledge in this 2nd edition include: Bedros Afeyan, Nabila Aghanim, Emmanuel Cand' es, David Donoho, Jalal Fadili, and Sandrine Pires, We would like to particularly - knowledge Olivier Forni who contributed to the discussion on compression of hyperspectral data, Yassir Moudden on multiwavelength data analysis and Vicent Mart' ?nez on the genus function. The cover image to this 2nd edition is from the Deep Impact project. It was taken approximately 8 minutes after impact on 4 July 2005 with the CLEAR6 ?lter and deconvolved using the Richardson-Lucy method. We thank Don Lindler, Ivo Busko, Mike A'Hearn and the Deep Impact team for the processing of this image and for providing it to us.

Video text detection provides an efficient approach to the indexing, classification, retrieval and understanding of visual content.

This unique text/reference presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis, and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems.

Topics and features: explains the fundamental theory in a succinct manner, supplemented with thorough, up-to-date references for further reading; highlights practical techniques to help the reader understand and develop their own detection systems and video text-based applications; discusses the state of the field from historical progress to the latest cutting-edge developments; serves as an easy-to-navigate reference, presenting the material in self-contained chapters; reviews the entire process from pre-processing to post-processing, including non-English script detection and advanced multi-modal techniques.

This accessible yet comprehensive overview of video text detection is essential reading for advanced students and researchers in pattern recognition, document analysis, image processing, video retrieval and related fields.

The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine. Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be achieved in varying illumination?"

This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a survey of the state-of-the-art, as well original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in its subject.

This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naive Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

This book takes you through all the basic steps of character design for games and animation, from brainstorming and references through to the development phase and final render. It covers a range of styles such as cartoon, stylized and semi-realistic, and explains how to differentiate between them and use them effectively. Using a step-by-step approach for each stage of the process, this book guides you through the process of creating a new character from scratch. It contains a wealth of design tips and tricks as well as checklists and worksheets for you to use in your own projects. The book covers how to work with briefs, as well as providing advice and practical strategies for working with clients and creating art as a product that can be tailored and sold. This book will be a valuable resource for all junior artists, hobby artists, and art students looking to develop and improve their character development skills for games and animation.

Provides a technical introduction to deepfakes, its benefits, and the potential harms Presents practical approaches of creation and detection of deepfakes using Deep Learning (DL) Techniques Draws attention towards various challenging issues and societal impact of deepfakes with their existing solutions Includes research analysis in the domain of DL fakes for assisting the creation and detection of deepfakes applications Discusses future research directions with emergence of deepfakes technology

If you want to know how to: * get the most from any image * retouch and edit photographs * prepare photographs for the web or print * quickly access the power of Photoshop * create special effects with text and images then Photoshop Made Simple is for you!

Description: This tutorial-based book allows readers to create a first-person game from start to finish using industry-standard (and free to student) tools of Maya, Substance Painter, and Unreal Engine. The first half of the book lays out the basics of using Maya and Substance Painter to create game-ready assets. This includes polygonal modeling, UV layout, and custom texture painting. Then, the book covers rigging and animation solutions to create assets to be placed in the game including animated first-person assets and motion-captured NPC animations. Finally, readers can put it all together and build interactivity that allows the player to create a finished game using the assets built and animated earlier in the book. * Written by industry professionals with real-world experience in building assets and games. * Build a complete game from start to finish. * Learn what the pros use: construct all assets using the tools used at industries across the world. * All software used are free to students. * When complete, students will have a playable version of an FPS game. Jing Tian Li is a graduate of China's Central Academy of Fine Arts and New York's School of Visual Arts, where he earned an MFA in Computer Art. He currently is an Assistant Professor of 3D Animation & Game Design at the University of the Incarnate Word in San Antonio, Texas. Kassandra Arevalo is an instructor of 3D Animation & Game Design at the University of the Incarnate Word in San Antonio, Texas. She previously worked as an animator at Immersed Games. Matt Tovar is an industry veteran animator. He has worked at Naughty Dog, Infinity Ward, and Sony Interactive on such games as The Last of Us, Call of Duty: Modern Warfare, and most recently Marvel's Avengers with Crystal Dynamics. He is an Assistant Professor of 3D Animation at the University of the Incarnate Word in San Antonio, Texas.

Multimedia surveillance systems is an emerging field that includes signal and image processing, communications, and computer vision. Multimedia Video-Based Surveillance Systems: Requirements, Issues and Solutions, combines the most recent research results from these areas for use by engineers and end-users involved in the design of surveillance systems in the fields of transportation and services. The book covers emerging surveillance requirements, including new digital sensors for real-time acquisition of surveillance data, low-level image processing algorithms, and event detection methods. It also discusses problems related to knowledge representation in surveillance systems, wireless and wired multimedia networks, and a new generation of surveillance communication tools. Timely information is presented on digital watermarking, broadband multimedia transmission, legal use of surveillance systems, performance evaluation criteria, and other new and emerging topics, along with applications for transports and pedestrian monitoring. The information contained in Multimedia Video-Based Surveillance Systems: Requirements, Issues and Solutions, bridges the distance between present practice and research findings, and the book is an indispensable reference tool for professional engineers.

The current popular and scientific interest in virtual environments has provided a new impetus for investigating binaural and spatial hearing. However, the many intriguing phenomena of spatial hearing have long made it an exciting area of scientific inquiry. Psychophysical and physiological investigations of spatial hearing seem to be converging on common explanations of underlying mechanisms. These understandings have in turn been incorporated into sophisticated yet mathematically tractable models of binaural interaction. Thus, binaural and spatial hearing is one of the few areas in which professionals are soon likely to find adequate physiological explanations of complex psychological phenomena that can be reasonably and usefully approximated by mathematical and physical models. This volume grew out of the Conference on Binaural and Spatial Hearing, a four-day event held at Wright-Patterson Air Force Base in response to rapid developments in binaural and spatial hearing research and technology. Meant to be more than just a proceedings, it presents chapters that are longer than typical proceedings papers and contain considerably more review material, including extensive bibliographies in many cases. Arranged into topical sections, the chapters represent major thrusts in the recent literature. The authors of the first chapter in each section have been encouraged to take a broad perspective and review the current state of literature. Subsequent chapters in each section tend to be somewhat more narrowly focused, and often emphasize the authors' own work. Thus, each section provides overview, background, and current research on a particular topic. This book is significant in that it reviews the important work during the past 10 to 15 years, and provides greater breadth and depth than most of the previous works.

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems.

Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Expert advice from several industrial professionals who have worked for some of the world's biggest tech and interactive companies. Best practices that not only prepare writers on how to apply their craft to new fields, but also prepare them for the common ambiguity they will find in corporate and start-up environments. Breakdown of platforms that shows how tech capabilities can fulfill content expectations and how content can fulfill tech expectations. Basic storytelling mechanics customized to today's popular technologies and traditional gaming platforms.

Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning.
This volume provides two important contributions to the area:
* a general description of the issues and alternatives in applying case-based reasoning to design, and
* a description of specific implementations of case-based design.
Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

This book is concerned with the processing of signals that have been sampled and digitized. The authors present algorithms for the optimization, random simulation, and numerical integration of probability densities for applications of Bayesian inference to signal processing. In particular, methods are developed for the computation of marginal densities and evidence, and are applied to previously intractable problems either involving large numbers of parameters or where the signal model is of a complex form. The emphasis is on the applications of these methods notably to the restoration of digital audio recordings and biomedical data. After a chapter which sets out the main principles of Bayesian inference applied to signal processing, subsequent chapters cover numerical approaches to these techniques, the use of Markov chain Monte Carlo methods, the identification of abrupt changes in data using the Bayesian piecewise linear model, and identifying missing samples in digital audio signals.

Within the field of game design, game balance can best be described as a black art. It is the process by which game designers make a game simultaneously fair for players while providing them just the right amount of difficulty to be both exciting and challenging without making the game entirely predictable. This involves a combination of mathematics, psychology, and occasionally other fields such as economics and game theory. Game Balance offers readers a dynamic look into game design and player theory. Throughout the book, relevant topics on the use of spreadsheet programs will be included in each chapter. This book therefore doubles as a useful reference on Microsoft Excel, Google Spreadsheets, and other spreadsheet programs and their uses for game designers. FEATURES The first and only book to explore game balance as a topic in depth Topics range from intermediate to advanced, while written in an accessible style that demystifies even the most challenging mathematical concepts to the point where a novice student of game design can understand and apply them Contains powerful spreadsheet techniques which have been tested with all major spreadsheet programs and battle-tested with real-world game design tasks Provides short-form exercises at the end of each chapter to allow for practice of the techniques discussed therein along with three long-term projects divided into parts throughout the book that involve their creation Written by award-winning designers with decades of experience in the field Ian Schreiber has been in the industry since 2000, first as a programmer and then as a game designer. He has worked on eight published game titles, training/simulation games for three Fortune 500 companies, and has advised countless student projects. He is the co-founder of Global Game Jam, the largest in-person game jam event in the world. Ian has taught game design and development courses at a variety of colleges and universities since 2006. Brenda Romero is a BAFTA award-winning game director, entrepreneur, artist, and Fulbright award recipient and is presently game director and creator of the Empire of Sin franchise. As a game director, she has worked on 50 games and contributed to many seminal titles, including the Wizardry and Jagged Alliance series and titles in the Ghost Recon, Dungeons & Dragons, and Def Jam franchises.

This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.