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.

The field of computer graphics combines display hardware, software, and interactive techniques in order to display and interact with data generated by applications. Visualization is concerned with exploring data and information graphically in such a way as to gain information from the data and determine significance. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces.

Expanding the Frontiers of Visual Analytics and Visualization provides a review of the state of the art in computer graphics, visualization, and visual analytics by researchers and developers who are closely involved in pioneering the latest advances in the field. It is a unique presentation of multi-disciplinary aspects in visualization and visual analytics, architecture and displays, augmented reality, the use of color, user interfaces and cognitive aspects, and technology transfer. It provides readers with insights into the latest developments in areas such as new displays and new display processors, new collaboration technologies, the role of visual, multimedia, and multimodal user interfaces, visual analysis at extreme scale, and adaptive visualization.

This book presents a comprehensive discussion on the characterization of vagueness in pictures. It reports on how the problem of representation of images has been approached in scientific practice, highlighting the role of mathematical methods and the philosophical background relevant for issues such as representation, categorization and reasoning. Without delving too much into the technical details, the book examines and defends different kinds of values of fuzziness based on a complex approach to categorization as a practice, adopting conceptual and empirical suggestions from different fields including the arts. It subsequently advances criticisms and provides suggestions for interpretation and application. By describing a cognitive framework based on fuzzy, rough and near sets, and discussing all of the relevant mathematical and philosophical theories for the representation and processing of vagueness in images, the book offers a practice-oriented guide to fuzzy visual reasoning, along with novel insights into the field of interpreting and thinking with fuzzy pictures and fuzzy data.

The first notable feature of this book is its innovation Computational intelligence (CI), a fast evolving area, is currently attracting lots of researchers' attention in dealing with many complex problems. At present, there are quite a lot competing books existing in the market. Nevertheless, the present book is markedly different from the existing books in that it presents new paradigms of CI that have rarely mentioned before, as opposed to the traditional CI techniques or methodologies employed in other books.During the past decade, a number of new CI algorithms are proposed. Unfortunately, they spread in a number of unrelated publishing directions which may hamper the use of such published resources. These provide us with motivation to analyze the existing research for categorizing and synthesizing it in a meaningful manner. The mission of this book is really important since those algorithms are going to be a new revolution in computer science. We hope it will stimulate the readers to make novel contributions or even start a new paradigm based on nature phenomena. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers and independent learners. We believe that the book will be instrumental in initiating an integrated approach to complex problems by allowing cross-fertilization of design principles from different design philosophies.

The second feature of this book is its comprehensiveness Through an extensive literature research, there are 134 innovative CI algorithms covered in this book.

Drawn to Life is a two-volume collection of the legendary lectures of long-time Disney animator Walt Stanchfield. For over 20 years, Walt mentored a new generation of animators at the Walt Disney Studios and influenced such talented artists such as Tim Burton, Brad Bird, Glen Keane, and Andreas Deja. His writing and drawings have become must-have lessons for fine artists, film professionals, animators, and students looking for inspiration and essential training in drawing and the art of animation. Written by Walt Stanchfield (1919–2000), who began work for the Walt Disney Studios in the 1950s. His work can be seen in films such as Sleeping Beauty, The Jungle Book, 101 Dalmatians, and Peter Pan. Edited by Disney Legend and Oscar®-nominated producer Don Hahn, whose credits include the classic Beauty and the Beast, The Lion King, and Hunchback of Notre Dame.

The contributions appearing in this volume are a snapshot of the different topics that were discussed during the Second Conference "Mathematics and Image Processing held at the University of Orl ans in 2010. They mainly concern, image reconstruction, texture extraction and image classification and involve a variety of different methods and applications. Therefore it was impossible to split the papers into generic groups which is why they are presented in alphabetic order. However they mainly concern: texture analysis (5 papers) with different techniques (variational analysis, wavelet and morphological component analysis, fractional Brownian fields), geometrical methods (2 papers ) for restoration and invariant feature detection, classification (with multifractal analysis), neurosciences imaging and analysis of Multi-Valued Images.

Modern life is increasingly relying on digital technology, which in turn runs on mathematics. However, this underlying math is hidden from us. That is mostly a good thing since we do not want to be solving equations and calculating fractions just to get things done in our everyday business. But the mathematical details do matter for anyone who wants to understand how stuff works, or wishes to create something new in the jungle of apps and algorithms. This book takes a look at the mathematical models behind weather forecasting, climate change prediction, artificial intelligence, medical imaging and computer graphics. The reader is expected to have only a curious mind; technical math skills are not needed for enjoying this text.

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

• Readers will gain an understanding of the optical technology, material science, and semiconductor device technology behind image acquisition devices • Research on image information is stable but slowly growing and several universities globally teach related courses for which this is valuable supplementary reading • This book offers a unique focus on the devices used in image sensors and displays

Traditional wireless sensor networks (WSNs) capture scalar data such as temperature, vibration, pressure, or humidity. Motivated by the success of WSNs and also with the emergence of new technology in the form of low-cost image sensors, researchers have proposed combining image and audio sensors with WSNs to form wireless multimedia sensor networks (WMSNs). This introduces practical and research challenges, because multimedia sensors, particularly image sensors, generate huge amounts of data to be processed and distributed within the network, while sensor nodes have restricted battery power and hardware resources. This book describes how reconfigurable hardware technologies such as field-programmable gate arrays (FPGAs) offer cost-effective, flexible platforms for implementing WMSNs, with a main focus on developing efficient algorithms and architectures for information reduction, including event detection, event compression, and multicamera processing for hardware implementations. The authors include a comprehensive review of wireless multimedia sensor networks, a complete specification of a very low-complexity, low-memory FPGA WMSN node processor, and several case studies that illustrate information reduction algorithms for visual event compression, detection, and fusion. The book will be of interest to academic researchers, R&D engineers, and computer science and engineering graduate students engaged with signal and video processing, computer vision, embedded systems, and sensor networks.

Game Audio Fundamentals takes the reader on a journey through game audio design: from analog and digital audio basics, to the art and execution of sound effects, soundtracks, and voice production, as well as learning how to make sense of a truly effective soundscape. Presuming no pre-existing knowledge, this accessible guide is accompanied by online resources - including practical examples and incremental DAW exercises - and presents the theory and practice of game audio in detail, and in a format anyone can understand. This is essential reading for any aspiring game audio designer, as well as students and professionals from a range of backgrounds, including music, audio engineering, and game design.

This textbook takes a case study approach to media and audience analytics. Realizing the best way to understand analytics in the digital age is to practice it, the authors have created a collection of cases using data sets that present real and hypothetical scenarios for students to work through. Media Analytics introduces the key principles of media economics and management. It outlines how to interpret and present results, the principles of data visualization and storytelling and the basics of research design and sampling. Although shifting technology makes measurement and analytics a dynamic space, this book takes an evergreen, conceptual approach, reminding students to focus on the principles and foundations that will remain constant. Aimed at upper-level students in the fast-growing area of media analytics in a cross-platform world, students using this text will learn how to find the stories in the data and to present those stories in an engaging way to others. Instructor and Student Resources include an Instructor's Manual, discussion questions, short exercises and links to additional resources. They are available online at www.routledge.com/cw/hollifield.

A definitive guide to contemporary video game studies, this second edition has been fully revised and updated to address the ongoing theoretical and methodological development of game studies. Expertly compiled by well-known video game scholars Mark J. P. Wolf and Bernard Perron, the Companion includes comprehensive and interdisciplinary models and approaches for analyzing video games, new perspectives on video games both as an art form and cultural phenomenon, explorations of the technical and creative dimensions of video games, and accounts of the political, social, and cultural dynamics of video games. Brand new to this second edition are essays examining topics such as preservation, augmented, mixed and virtual reality, eSports, disability, diversity, and identity, as well as a new section that specifically examines the industrial aspects of video games including digital distribution, game labor, triple-A games, indie games, and globalization. Each essay provides a lively and succinct summary of its target area, quickly bringing the reader up-to-date on the pertinent issues surrounding each aspect of the field, including references for further reading. A comprehensive overview of the present state of video game studies that will undoubtedly prove invaluable to students, scholars, and game designers alike.

This anthology contributes to creating awareness on how digital ageism operates in relation to the widely spread symbolic representations of old and young age, the (lack of) representation of diverse older individuals in the design, development, and discourses and in the actual algorithms and datasets. It also shows how individuals and institutions deal with digital ageism in everyday life. In the past decades, digital technologies permeated most aspects of everyday life and became ingrained into human existence. With a focus on how age is represented and experienced in relation to digital technologies leading to digital ageism, digitalisation's reinforcement of spirals of exclusion and loss of autonomy of some collectives is explored, when it could be natural for a great part of society and represent a sort of improvement. The book addresses social science students and scholars interested in everyday digital technologies, society and the power struggles about it, providing insights from different parts of the globe. By using different methods and touching upon different aspects of digital ageism and how it plays out in contemporary connected data societies, this volume will raise awareness, challenge power, initiate discussions and spur further research into this field.

The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in Electrical Engineering. The first edition of this book was published in 2014. As there is a demand for the next edition, it is quite natural to take note of the several advances that have occurred in the subject over the past five years. This is the prime motivation for bringing out a revised second edition with a thorough revision of all the chapters. The book presents a clear and comprehensive introduction to signals and systems. For easier comprehension, the course contents of all the chapters are in sequential order. Analysis of continuous-time and discrete-time signals and systems are done separately for easy understanding of the subjects. The chapters contain over seven hundred numerical examples to understand various theoretical concepts. This textbook also includes numerical examples that were appeared in recent examinations and presented in a graded manner. The topics such as the representation of signals, convolution, Fourier Series and Fourier Transform, Laplace transform, Z-transform, and state-space analysis are explained with a large number of numerical examples in the book. The detailed coverage and pedagogical tools make this an ideal textbook for students and researchers enrolled in electrical engineering and related courses.

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.

Working with Sound is an exploration of the ever-changing working practices of audio development in the era of hybrid collaboration in the games industry. Through learnings from the pre-pandemic remote and isolated worlds of audio work, sound designers, composers and dialogue designers find themselves equipped uniquely to thrive in the hybrid, remote, and studio-based realms of today's fast-evolving working landscapes. With unique insights into navigating the worlds of isolation and collaboration, this book explores ways of thinking and working in this world, equipping the reader with inspiration to sustainably tackle the many stages of the development process. Working with Sound is an essential guide for professionals working in dynamic audio teams of all sizes, as well as the designers, producers, artists, animators and programmers who collaborate closely with their colleagues working on game audio and sound.

This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.

This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.

The Game Music Toolbox provides readers with the tools, models and techniques to create and expand a compositional toolbox, through a collection of 20 iconic case studies taken from different eras of game music. Discover many of the composition and production techniques behind popular music themes from games such as Cyberpunk 2077, Mario Kart 8, The Legend of Zelda, Street Fighter II, Diablo, Shadow of the Tomb Raider, The Last of Us, and many others. The Game Music Toolbox features: Exclusive interviews from industry experts Transcriptions and harmonic analyses 101 music theory introductions for beginners Career development ideas and strategies Copyright and business fundamentals An introduction to audio implementation for composers Practical takeaway tasks to equip readers with techniques for their own game music The Game Music Toolbox is crucial reading for game music composers and audio professionals of all backgrounds, as well as undergraduates looking to forge a career in the video game industry.

The book augurs to be a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives orient to offer an overview to the elementary concepts and practices appropriate to DIP as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to: Applications and tools for image processing, fundamentals with several implementation examples Concepts of image formation, OpenCV installation with step-by-step screen shots Concepts behind intensity, brightness and contrast, color models Ways by which noises are created in an image and the possible remedial measures Edge detection, Image segmentation, classification, regression, Classification algorithms Importance of frequency domain in image processing field Relevant code snippets and the MATLAB codes, several interesting set of simple programs in OpenCV and Python to aid learning and for complete understanding The video lectures for specific topics through YouTube by the authors enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quiz, review questions etc., fully prepares the readers for further study. Graduate Students, Post Graduate students, Researchers, and anyone in general interested in Image Processing, Computer Vision, Machine Learning domains etc. can find this book an excellent starting point for information and as an able ally.

The text covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. The book- Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems Highlight privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. Discusses nature-inspired computing algorithms for the brain-computer interface. Covers graph neural network application in the medical domain. Provides insights into the state-of-the-art Artificial Intelligence and Smart Computing enabling and emerging technologies. This book text discusses recent advances and applications of artificial intelligence and smart technologies in the field of healthcare. It highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. It covers nature-inspired computing algorithms such as genetic algorithms, particle swarm optimization algorithms, and common scrambling algorithms to study brain-computer interfaces. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

- Written by a team of scholars who developed the first major Black Digital Humanities program at a research institution (the African American Digital Humanities Initiative at the University of Maryland). - Written for an audience of practitioners, researchers, and graduate students to help prepare them to take on their own research and projects. - Each chapter features guiding questions, bullet lists of practical advice, and resources readers can use to implement best practices in their own work.