Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4) human-computer affective multimedia interaction. Its 15 chapters cover key topics such as content creation, annotation and modeling for the semantic web, multimedia content understanding, and efficiency and scalability. Fostering a deeper understanding of a popular area of research, the text: Describes state-of-the-art schemes and applications Supplies authoritative guidance on research and deployment issues Presents novel methods and applications in an informative and reproducible way Contains numerous examples, illustrations, and tables summarizing results from quantitative studies Considers ongoing trends and designates future challenges and research perspectives Includes bibliographic links for further exploration Uses both SI and US units Ideal for engineers and scientists specializing in the design of multimedia systems, software applications, and image/video analysis and processing technologies, Semantic Multimedia Analysis and Processing aids researchers, practitioners, and developers in finding innovative solutions to existing problems, opening up new avenues of research in uncharted waters.

Image Restoration: Fundamentals and Advances responds to the need to update most existing references on the subject, many of which were published decades ago. Providing a broad overview of image restoration, this book explores breakthroughs in related algorithm development and their role in supporting real-world applications associated with various scientific and engineering fields. These include astronomical imaging, photo editing, and medical imaging, to name just a few. The book examines how such advances can also lead to novel insights into the fundamental properties of image sources. Addressing the many advances in imaging, computing, and communications technologies, this reference strikes just the right balance of coverage between core fundamental principles and the latest developments in this area. Its content was designed based on the idea that the reproducibility of published works on algorithms makes it easier for researchers to build on each other's work, which often benefits the vitality of the technical community as a whole. For that reason, this book is as experimentally reproducible as possible. Topics covered include: Image denoising and deblurring Different image restoration methods and recent advances such as nonlocality and sparsity Blind restoration under space-varying blur Super-resolution restoration Learning-based methods Multi-spectral and color image restoration New possibilities using hybrid imaging systems Many existing references are scattered throughout the literature, and there is a significant gap between the cutting edge in image restoration and what we can learn from standard image processing textbooks. To fill that need but avoid a rehash of the many fine existing books on this subject, this reference focuses on algorithms rather than theories or applications. Giving readers access to a large amount of downloadable source code, the book illustrates fundamental techniques, key ideas developed over the years, and the state of the art in image restoration. It is a valuable resource for readers at all levels of understanding.

As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins with a section on standards, fundamental methods, design issues, and typical architectures. It then focuses on the coding of video and multimedia content before covering multimedia search, retrieval, and management. After examining multimedia security, the book describes multimedia communications and networking and explains the architecture design and implementation for multimedia image and video processing. It concludes with a section on multimedia systems and applications. Written by some of the most prominent experts in the field, this updated edition provides readers with the latest research in multimedia processing and equips them with advanced techniques for the design of multimedia systems.

Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drastic increase in the number of applications based on digital images. This book explores how graphs-which are suitable to represent any discrete data by modeling neighborhood relationships-have emerged as the perfect unified tool to represent, process, and analyze images. It also explains why graphs are ideal for defining graph-theoretical algorithms that enable the processing of functions, making it possible to draw on the rich literature of combinatorial optimization to produce highly efficient solutions. Some key subjects covered in the book include: Definition of graph-theoretical algorithms that enable denoising and image enhancement Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov Random Fields Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets Analysis of the similarity between objects with graph matching Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging Use of graphs has become very influential in computer science and has led to many applications in denoising, enhancement, restoration, and object extraction. Accounting for the wide variety of problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

The book has two intentions. First, it assembles the latest research in the field of medical imaging technology in one place. Detailed descriptions of current state-of-the-art medical imaging systems (comprised of x-ray CT, MRI, ultrasound, and nuclear medicine) and data processing techniques are discussed. Information is provided that will give interested engineers and scientists a solid foundation from which to build with additional resources. Secondly, it exposes the reader to myriad applications that medical imaging technology has enabled.

"John Russ is the master of explaining how image processing gets applied to real-world situations. With Brent Neal, he's done it again in Measuring Shape, this time explaining an expanded toolbox of techniques that includes useful, state-of-the-art methods that can be applied to the broad problem of understanding, characterizing, and measuring shape. He has a gift for finding the kernel of a particular algorithm, explaining it in simple terms, then giving concrete examples that are easily understood. His perspective comes from solving real-world problems and separating out what works in practice from what is just an abstract curiosity." -Tom Malzbender, Hewlett-Packard Laboratories, Palo Alto, California, USA Useful for those working in fields including industrial quality control, research, and security applications, Measuring Shape is a handbook for the practical application of shape measurement. Covering a wide range of shape measurements likely to be encountered in the literature and in software packages, this book presents an intentionally diverse set of examples that illustrate and enable readers to compare methods used for measurement and quantitative description of 2D and 3D shapes. It stands apart through its focus on examples and applications, which help readers quickly grasp the usefulness of presented techniques without having to approach them through the underlying mathematics. An elusive concept, shape is a principal governing factor in determining the behavior of objects and structures. Essential to recognizing and classifying objects, it is the central link in manmade and natural processes. Shape dictates everything from the stiffness of a construction beam, to the ability of a leaf to catch water, to the marketing and packaging of consumer products. This book emphasizes techniques that are quantitative and produce a meaningful yet compact set of numerical values that can be used for statistical analysis, comparison, correlation, classification, and identification. Written by two renowned authors from both industry and academia, this resource explains why users should select a particular method, rather than simply discussing how to use it. Showcasing each process in a clear, accessible, and well-organized way, they explore why a particular one might be appropriate in a given situation, yet a poor choice in another. Providing extensive examples, plus full mathematical descriptions of the various measurements involved, they detail the advantages and limitations of each method and explain the ways they can be implemented to discover important correlations between shape and object history or behavior. This uncommon assembly of information also includes sets of data on real-world objects that are used to compare the performance and utility of the various presented approaches.

The first edition of this text book focussed on providing practical hands-on experience in digital imaging techniques for graduate students and practitioners keeping to a minimum any detailed discussion on the underlying theory. In this new extended edition, the author builds on the strength of the original edition by expanding the coverage to include formulation of the major theoretical results that underlie the exercises as well as introducing numerous modern concepts and new techniques. Whether you are studying or already using digital imaging techniques, developing proficiency in the subject is not possible without mastering practical skills. Including more than 100 MATLAB (R) exercises, this book delivers a complete applied course in digital imaging theory and practice.

This textbook covers the theoretical backgrounds and practical aspects of image, video and audio feature expression, e.g., color, texture, edge, shape, salient point and area, motion, 3D structure, audio/sound in time, frequency and cepstral domains, structure and melody. Up-to-date algorithms for estimation, search, classification and compact expression of feature data are described in detail. Concepts of signal decomposition (such as segmentation, source tracking and separation), as well as composition, mixing, effects, and rendering, are discussed. Numerous figures and examples help to illustrate the aspects covered. The book was developed on the basis of a graduate-level university course, and most chapters are supplemented by problem-solving exercises. The book is also a self-contained introduction both for researchers and developers of multimedia content analysis systems in industry.

This book constitutes selected, revised and extended papers from the 13th International Conference on Computer Supported Education, CSEDU 2021, held as a virtual event in April 2021. The 27 revised full papers were carefully reviewed and selected from 143 submissions. They were organized in topical sections as follows: artificial intelligence in education; information technologies supporting learning; learning/teaching methodologies and assessment; social context and learning environments; ubiquitous learning; current topics.

The Definitive Vulkan (TM) Developer's Guide and Reference: Master the Next-Generation Specification for Cross-Platform Graphics The next generation of the OpenGL specification, Vulkan, has been redesigned from the ground up, giving applications direct control over GPU acceleration for unprecedented performance and predictability. Vulkan (TM) Programming Guide is the essential, authoritative reference to this new standard for experienced graphics programmers in all Vulkan environments. Vulkan API lead Graham Sellers (with contributions from language lead John Kessenich) presents example-rich introductions to the portable Vulkan API and the new SPIR-V shading language. The author introduces Vulkan, its goals, and the key concepts framing its API, and presents a complex rendering system that demonstrates both Vulkan's uniqueness and its exceptional power. You'll find authoritative coverage of topics ranging from drawing to memory, and threading to compute shaders. The author especially shows how to handle tasks such as synchronization, scheduling, and memory management that are now the developer's responsibility. Vulkan (TM) Programming Guide introduces powerful 3D development techniques for fields ranging from video games to medical imaging, and state-of-the-art approaches to solving challenging scientific compute problems. Whether you're upgrading from OpenGL or moving to open-standard graphics APIs for the first time, this guide will help you get the results and performance you're looking for. Coverage includes Extensively tested code examples to demonstrate Vulkan's capabilities and show how it differs from OpenGL Expert guidance on getting started and working with Vulkan's new memory system Thorough discussion of queues, commands, moving data, and presentation Full explanations of the SPIR-V binary shading language and compute/graphics pipelines Detailed discussions of drawing commands, geometry and fragment processing, synchronization primitives, and reading Vulkan data into applications A complete case study application: deferred rendering using complex multi-pass architecture and multiple processing queues Appendixes presenting Vulkan functions and SPIR-V opcodes, as well as a complete Vulkan glossary

This volume aims to stimulate discussions on research involving the use of data and digital images as an understanding approach for analysis and visualization of phenomena and experiments. The emphasis is put not only on graphically representing data as a way of increasing its visual analysis, but also on the imaging systems which contribute greatly to the comprehension of real cases.

Scientific Visualization and Imaging Systems encompass multidisciplinary areas, with applications in many knowledge fields such as Engineering, Medicine, Material Science, Physics, Geology, Geographic Information Systems, among others.

This book is a selection of 13 revised and extended research papers presented in the International Conference on Advanced Computational Engineering and Experimenting -ACE-X conferences 2010 (Paris), 2011 (Algarve), 2012 (Istanbul) and 2013 (Madrid). The examples were particularly chosen from materials research, medical applications, general concepts applied in simulations and image analysis and other interesting related problems.

The main subject of the monograph is the fractional calculus in the discrete version. The volume is divided into three main parts. Part one contains a theoretical introduction to the classical and fractional-order discrete calculus where the fundamental role is played by the backward difference and sum. In the second part, selected applications of the discrete fractional calculus in the discrete system control theory are presented. In the discrete system identification, analysis and synthesis, one can consider integer or fractional models based on the fractional-order difference equations. The third part of the book is devoted to digital image processing.

In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book. Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally. The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization. Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling.

This book offers a comprehensive introduction to seven commonly used image understanding techniques in modern information technology. Readers of various levels can find suitable techniques to solve their practical problems and discover the latest development in these specific domains. The techniques covered include camera model and calibration, stereo vision, generalized matching, scene analysis and semantic interpretation, multi-sensor image information fusion, content-based visual information retrieval, and understanding spatial-temporal behavior. The book provides aspects from the essential concepts overview and basic principles to detailed introduction, explanation of the current methods and their practical techniques. It also presents discussions on the research trends and latest results in conjunction with new development of technical methods. This is an excellent read for those who do not have a subject background in image technology but need to use these techniques to complete specific tasks. These essential information will also be useful for their further study in the relevant fields.

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation. The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media. While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book. Introducing SAR imaging from a systems point of view, the author: Considers the recent development of MIMO SAR technology Includes selected GPU implementation Provides a numerical analysis of system parameters (including platforms, sensor, and image focusing, and their influence) Explores wave-target interactions, signal transmission and reception, image formation, motion compensation Covers all platform motion compensation and error analysis, and their impact on final image radiometric and geometric quality Describes a ground-based SFMCW system Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach is dedicated to the use, study, and development of SAR systems. The book focuses on image formation or focusing, treats platform motion and image focusing, and is suitable for students, radar engineers, and microwave remote sensing researchers.

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms

VipIMAGE 2015 contains invited lectures and full papers presented at VIPIMAGE 2015 - V ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (Tenerife, Canary Islands, Spain, 19-21 October, 2015). International contributions from 19 countries provide a comprehensive coverage of the current state-of-the-art in the fields of: 3D Vision; Computational Bio-Imaging and Visualization; Computational Vision; Computer Aided Diagnosis, Surgery, Therapy and Treatment; Data Interpolation, Registration, Acquisition and Compression; Industrial Inspection; Image Enhancement; Image Processing and Analysis; Image Segmentation; Medical Imaging; Medical Rehabilitation; Physics of Medical Imaging; Shape Reconstruction; Signal Processing; Simulation and Modelling; Software Development for Image Processing and Analysis; Telemedicine Systems and their Applications; Tracking and Analysis of Movement and Deformation; Virtual Reality. Computational Vision and Medical Image Processing. VipIMAGE 2015 will be useful to academics, researchers and professionals in Biomechanics, Biomedical Engineering, Computational Vision (image processing and analysis), Computer Sciences, Computational Mechanics, Signal Processing, Medicine and Rehabilitation.

1) Engineering approach, applications oriented 2) Numerous examples and exercises to illustrate concepts and their implementation 3) Clearly written and concise 4) Learn concepts so that the reader can develop their own algorithms 5) Software tools provided for both C and Matlab

The slime mould Physarum polycephalum is a large cell visible by the unaided eye. It behaves as an intelligent nonlinear spatially extended active medium encapsulated in an elastic membrane. The cell optimises its growth patterns in configurations of attractants and repellents. This behaviour is interpreted as computation. Numerous prototypes of slime mould computers were designed to solve problems of computational geometry, graphs and transport networks and to implement universal computing circuits.In this unique set of scientific photographs and micrographs, the leading experts in computer science, biology, chemistry and material science illustrate in superb detail the nature of the slime mould computers and hybrid devices. Every photograph or micrograph in this book is of real scientific, theoretical or technological interest. Each entry includes a self-contained description of how the visualised phenomenon is used in the relevant slime mould computer. This atlas is unique in providing the depth and breadth of knowledge in harnessing behaviour of the slime mould to perform computation. It will help readers to understand how exploitation of biological processes has sparked new ideas and spurred progress in many fields of science and engineering.

- the book can be used by beginners in the field, tracking from basic principles to how to bend the rules, in reader-friendly language throughout - the book is based on a popular blog which dovetails as a fantastic companion website: https://questionsindataviz.com/ - the author is a very experienced and well-respected practitioner in the field, with a good-size following on social media: https://twitter.com/theneilrichards

This interdisciplinary study participates in the ongoing critical conversation about postwar American poetry and visual culture, while advancing that field into the arena of the museum. Turning to contemporary poems about the visual arts that foreground and interrogate a museum setting, the book demonstrates the particular importance of the museum as a cultural site that is both inspiration and provocation for poets. The study uniquely bridges the "dual canon" in contemporary poetry (and calls the lyric/avant-garde distinction into question) by analyzing museum-sponsored anthologies as well as poems by John Ashbery, Richard Howard, Kenneth Koch, Kathleen Fraser, Cole Swensen, Anne Carson, and others. Through these case studies of poets with diverse affiliations, the author shows that the boom in ekphrasis in the past 20 years is not only an aesthetic but a critical phenomenon, a way that poets have come to terms with the critical dilemmas of our moment. Highlighting the importance of poets' "peripheral vision"-awareness of the institutional conditions that frame encounters with art-the author contend that a museum visit becomes a forum for questioning oppositions that have preoccupied literary criticism for the past 50 years: homage and innovation, modernism and postmodernism, subjectivity and collectivity. The study shows that ekphrasis becomes a strategy for negotiating these impasses-a mode of political inquiry, a meditation on canonization, a venue for comic appraisal of institutionalization, and a means of "site-specific" feminist revision-in a vital synthesis of critique, perspicacity, and pleasure.

This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures.

Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques

Image and video signals require large transmission bandwidth and storage, leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus, efficient image and video compression algorithms play a significant role in the storage and transmission of data. Image and Video Compression: Fundamentals, Techniques, and Applications explains the major techniques for image and video compression and demonstrates their practical implementation using MATLAB (R) programs. Designed for students, researchers, and practicing engineers, the book presents both basic principles and real practical applications. In an accessible way, the book covers basic schemes for image and video compression, including lossless techniques and wavelet- and vector quantization-based image compression and digital video compression. The MATLAB programs enable readers to gain hands-on experience with the techniques. The authors provide quality metrics used to evaluate the performance of the compression algorithms. They also introduce the modern technique of compressed sensing, which retains the most important part of the signal while it is being sensed.