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.

[FIRST EDITION] This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Features: introduces the mathematical background for monocular and multiple view geometry; describes the main techniques for image processing used in X-ray testing; presents a range of different representations for X-ray images, explaining how these enable new features to be extracted from the original image; examines a range of known X-ray image classifiers and classification strategies; discusses some basic concepts for the simulation of X-ray images and presents simple geometric and imaging models that can be used in the simulation; reviews a variety of applications for X-ray testing, from industrial inspection and baggage screening to the quality control of natural products; provides supporting material at an associated website, including a database of X-ray images and a Matlab toolbox for use with the book's many examples.

This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a tutorial of basic concepts and techniques of deep learning. In addition, the book systematically investigates the main human centric analysis tasks of different levels, ranging from detection and segmentation to parsing and higher-level understanding. At last, it presents the state-of-the-art solutions based on deep learning for every task, as well as providing sufficient references and extensive discussions. Specifically, this book addresses four important research topics, including 1) localizing persons in images, such as face and pedestrian detection; 2) parsing persons in details, such as human pose and clothing parsing, 3) identifying and verifying persons, such as face and human identification, and 4) high-level human centric tasks, such as person attributes and human activity understanding. This book can serve as reading material and reference text for academic professors / students or industrial engineers working in the field of vision surveillance, biometrics, and human-computer interaction, where human centric visual analysis are indispensable in analysing human identity, pose, attributes, and behaviours for further understanding.

The advancement of security technologies has allowed information systems to store more crucial and sensitive data. With these advancements, organisations turn to physiological and behavioral methods of identification in order to guard against unwanted intrusion. Research Developments in Biometrics and Video Processing Techniques investigates advanced techniques in user identification and security, including retinal, facial, and finger print scans as well as signature and voice authentication models. Through its in-depth examination of computer vision applications and other biometric security technologies, this reference volume will provide researchers, engineers, developers, and students with insight into the latest research on enhanced security systems design and development.

In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.

Image and signal processing techniques are receiving increasing interest because of their numerous real-world applications. Data is now available in different forms, different wavelengths, and even in different dimensions, creating the need for novel multidisciplinary solutions for automated data processing and analysis. Applied Signal and Image Processing: Multidisciplinary Advancements highlights the growing multidisciplinary nature of signal and image processing by focusing on emerging applications and recent advances in well-established fields. This book covers state-or-the-art applications in both signal and image processing, which include optical communication and sensing, wireless communication management, face recognition and facial imaging, solar imaging and feature detection, fractal analysis, and video processing.

This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.

This book shows how the web-based PhysGL programming environment (http://physgl.org) can be used to teach and learn elementary mechanics (physics) using simple coding exercises. The book's theme is that the lessons encountered in such a course can be used to generate physics-based animations, providing students with compelling and self-made visuals to aid their learning. Topics presented are parallel to those found in a traditional physics text, making for straightforward integration into a typical lecture-based physics course. Users will appreciate the ease at which compelling OpenGL-based graphics and animations can be produced using PhysGL, as well as its clean, simple language constructs. The author argues that coding should be a standard part of lower-division STEM courses, and provides many anecdotal experiences and observations, that include observed benefits of the coding work.

This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition and analysis of signals and images, cardiovascular informatics, and mathematical and computational modeling.

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis. The book is directed to the Ph.D. students, professors, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

This book presents the latest advances in photometric 3D reconstruction. It provides the reader with an overview of the state of the art in the field, and of the latest research into both the theoretical foundations of photometric 3D reconstruction and its practical application in several fields (including security, medicine, cultural heritage and archiving, and engineering). These techniques play a crucial role within such emerging technologies as 3D printing, since they permit the direct conversion of an image into a solid object. The book covers both theoretical analysis and real-world applications, highlighting the importance of deepening interdisciplinary skills, and as such will be of interest to both academic researchers and practitioners from the computer vision and mathematical 3D modeling communities, as well as engineers involved in 3D printing. No prior background is required beyond a general knowledge of classical computer vision models, numerical methods for optimization, and partial differential equations.

This textbook guides readers through their first steps into the challenging world of mimicking human vision with computational tools and techniques pertaining to the field of image processing and analysis. While today's theoretical and applied processing and analysis of images meet with challenging and complex problems, this primer is confined to a much simpler, albeit critical, collection of image-to-image transformations, including image normalisation, enhancement, and filtering.It serves as an introduction to beginners, a refresher for undergraduate and graduate students, as well as engineers and computer scientists confronted with a problem to solve in computer vision. The book covers basic image processing/computer vision pipeline techniques, which are widely used in today's computer vision, computer graphics, and image processing, giving the readers enough knowledge to successfully tackle a wide range of applied problems.

As the most natural and convenient means of conveying or transmitting information, images play a vital role in our daily lives. Image processing is now of paramount importance in the computer vision research community, and proper processing of two-dimensional (2D) real-life images plays a key role in many real-life applications as well as commercial developments. Intelligent Multidimensional Data and Image Processing is a vital research publication that contains an in-depth exploration of image processing techniques used in various applications, including how to handle noise removal, object segmentation, object extraction, and the determination of the nearest object classification and its associated confidence level. Featuring coverage on a broad range of topics such as object detection, machine vision, and image conversion, this book provides critical research for scientists, computer engineers, professionals, researchers, and academicians seeking current research on solutions for new challenges in 2D and 3D image processing.

This book contains high-quality research articles and reviews that promote research and reflect the most recent advances in intelligent wavelet based techniques for advanced multimedia applications as well as other emerging areas. In recent time, wavelet transforms have become useful in many signal, image and video processing applications, especially for multimedia security and surveillance. A few applications of wavelets in security and surveillance are watermarking, fusion, steganography, object detection, tracking, motion recognition and intention recognition, etc. Wavelets are well capable of analyzing signal, image and video at different resolution levels, popularly known as multiresolution analysis. The multiresolution analysis is advantageous in multimedia security and surveillance applications. It provides flexibility in selection of different resolution levels that leads to better accuracy. Furthermore, recently sparse representation has become an advancement to analyze wavelet coefficients. It is observed that wavelet transforms possess the invariance property which makes them suitable for many vision applications. This book provides a concise overview of the current state of the art and disseminates some of the novel and exciting ideas and techniques. In addition, it is also helpful for the senior undergraduate and graduate students, researcher, academicians, IT professional and providers, citizens, customers as well as policy makers working in this area as well as other emerging applications demanding state-of-the-art wavelet based multimedia applications.

With the technology innovations dentistry has witnessed in all its branches over the past three decades, the need for more precise diagnostic tools and advanced imaging methods has become mandatory across the industry. Recent advancements to imaging systems are playing an important role in efficient diagnoses, treatments, and surgeries. Computational Techniques for Dental Image Analysis provides innovative insights into computerized methods for automated analysis. The research presented within this publication explores pattern recognition, oral pathologies, and diagnostic processing. It is designed for dentists, professionals, medical educators, medical imaging technicians, researchers, oral surgeons, and students, and covers topics centered on easier assessment of complex cranio-facial tissues and the accurate diagnosis of various lesions at early stages.

RUNS, JUMPS AND SKIPS From Richard Williams' The Animator's Survival Kit comes key chapters in mini form. The Animator's Survival Kit is the essential tool for animators. However, sometimes you don't want to carry the hefty expanded edition around with you to your college or studio if you're working on just one aspect of it that day. The Animation Minis take some of the most essential chapters and make them available in smaller, lightweight, hand-bag/backpack size versions. Easy to carry. Easy to study. This Mini focuses on Runs, Jumps and Skips. As with Walks, the way we run shows our character and personality. A lazy, heavy person is going to run very differently to an athletic ten-year-old girl. Richard Williams demonstrates how - when you're doing a walk and you take both legs off the ground, at the same time and for just one frame - a walk becomes a run. So, all the things we do with walks, we can do with runs. This Mini presents a collection of Williams' runs, jumps and skips inspired by some of the cleverest artists from the Golden Age of Animation

Technological advancements have created novel applications for image and video processing. With these developments, real-world processing problems can be solved more easily. The Handbook of Research on Advanced Concepts in Real-Time Image and Video Processing is a pivotal reference source for the latest research findings on the design, realization, and deployment of image and video processing systems meant for real-time environments. Featuring extensive coverage on relevant areas such as feature detection, reconfigurable computing, and stream processing, this publication is an ideal resource for academics, researchers, graduate students, and technology developers.

The computer graphics (CG) industry is an attractive field for undergraduate students, but employers often find that graduates of CG art programmes are not proficient. The result is that many positions are left vacant, despite large numbers of job applicants. This book investigates how student CG artists develop proficiency. The subject is important to the rapidly growing number of educators in this sector, employers of graduates, and students who intend to develop proficiency for the purpose of obtaining employment. Educators will see why teaching software-oriented knowledge to students does not lead to proficiency, but that the development of problem-solving and visualisation skills do. This book follows a narrow focus, as students develop proficiency in a cognitively challenging task known as 'NURBS modelling'. This task was chosen due to an observed relationship between students who succeeded in the task, and students who successfully obtained employment after graduation. In the study this is based on, readers will be shown that knowledge-based explanations for the development of proficiency do not adequately account for proficiency or expertise in this field, where visualisation has been observed to develop suddenly rather than over an extended period of time. This is an unusual but not unique observation. Other studies have shown rapid development of proficiency and expertise in certain professions, such as among telegraph operators, composers and chess players. Based on these observations, the book argues that threshold concepts play a key role in the development of expertise among CG artists.

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text presents a diverse selection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition. Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presents a technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods. This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding.

This book gathers selected papers presented at the conference "Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology," one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas. The aim of the conference was to establish a platform for experts to combine their efforts and share their ideas in the related areas in order to promote and accelerate future development. This second volume discusses algorithms and applications, focusing mainly on the following topics: 3D printing technologies; naked, dynamic and auxiliary 3D displays; VR/AR/MR devices; VR camera technologies; microprocessors for 3D data processing; advanced 3D computing systems; 3D data-storage technologies; 3D data networks and technologies; 3D data intelligent processing; 3D data cryptography and security; 3D visual quality estimation and measurement; and 3D decision support and information systems.

Written based on the author's own notes compiled over 18 years This manual is a learning tool focusing exclusively on the work of animators. explains the principles of physics applicable to any motion

This book constitutes the refereed proceedings of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, held virtually and in Hersonissos, Crete, Greece, in June 2021. The 50 full papers and 11 short papers presented were carefully reviewed and selected from 113 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: adaptive modeling/ neuroscience; AI in biomedical applications; AI impacts/ big data; automated machine learning; autonomous agents; clustering; convolutional NN; data mining/ word counts; deep learning; fuzzy modeling; hyperdimensional computing; Internet of Things/ Internet of energy; machine learning; multi-agent systems; natural language; recommendation systems; sentiment analysis; and smart blockchain applications/ cybersecurity. Chapter "Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-based Approaches: Challenges and Perspective" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.