Augmented Reality (AR) refers to the merging of a live view of the physical, real world with context-sensitive, computer-generated images to create a mixed reality. Through this augmented vision, a user can digitally interact with and adjust information about their surrounding environment on-the-fly. "Handbook of Augmented Reality" provides an extensive overview of the current and future trends in Augmented Reality, and chronicles the dramatic growth in this field. The book includes contributions from world expert s in the field of AR from academia, research laboratories and private industry. Case studies and examples throughout the handbook help introduce the basic concepts of AR, as well as outline the Computer Vision and Multimedia techniques most commonly used today. The book is intended for a wide variety of readers including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students. This book can also be beneficial for business managers, entrepreneurs, and investors.

This volume is about ultra high-speed cameras, which enable us to see what we normally do not see. These are objects that are moving very fast, or that we just ignore. Ultra high-speed cameras invite us to a wonderland of microseconds. There Alice (the reader) meets a ultra high-speed rabbit (this volume) and travels together through this wonderland from the year 1887 to 2017. They go to the horse riding ground and see how a horse gallops. The rabbit takes her to a showroom where various cameras and illumination devices are presented. Then, he sends Alice into semiconductor labyrinths, wind tunnels, mechanical processing factories, and dangerous explosive fields. Sometimes Alice is large, and at other times she is very small. She sits even inside a car engine. She falls down together with a droplet. She enters a microbubble, is thrown out with a jet stream, and finds herself in a human body. Waking up from her dream, she sees children playing a game: "I see what you do not see, and this is....". Alice thinks: "The ultra high-speed rabbit showed me many things which I had never seen. Now I will go again to this wonderland, and try to find something new.

This is a handbook of Gamma-convergence, which is a theoretical tool used to study problems in Applied Mathematics where varying parameters are present, with many applications that range from Mechanics to Computer Vision. The book is directed to Applied Mathematicians in all fields and to Engineers with a theoretical background.

Making a Machine That Sees Like Us explains why and how our visual perceptions can provide us with an accurate representation of the external world. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. This accomplishment required a radical paradigm shift - one that challenged preconceptions about visual perception and tested the limits of human behavior-modeling for practical application.
The text balances scientific sophistication and compelling storytelling, making it accessible to both technical and general readers. Online demonstrations and references to the authors' previously published papers detail how the machine was developed and what drove the ideas needed to make it work. The authors contextualize their new theory of shape perception by highlighting criticisms and opposing theories, offering readers a fascinating account not only of their revolutionary results, but of the scientific process that guided the way.

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics. It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.

The field of mechatronics (which is the synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and manufacturing processes) is gaining much attention in industries and academics. It was detected that the topics of computer vision, control and robotics are imperative for the successful of mechatronics systems. This book includes several chapters which report successful study cases about computer vision, control and robotics. The readers will have the latest information related to mechatronics, that contains the details of implementation, and the description of the test scenarios.

This book deepens the understanding of people through smartphone data obtained via mobile sensing and applies psychological insights for social networking applications. The author first introduces TYDR, an application for researching smartphone data and user personality. A novel, structured privacy model for mobile sensing applications is developed and the obtained empirical results help researchers gauge what data they can expect users to share in daily-life studies. The new research findings, the concept of mobile sensing, and psychological insights about the formation and structure of real-life social networks are integrated into the field of social networking. Finally, for this novel integration, the author presents concepts, decentralized software architectures, and fully realized prototypes that recommend new contacts, media, and locations to individual users and groups of users.

This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. Presents solutions to email spam detection and discusses its challenges such as text classification and categorization; Analyzes the proposed techniques' performance using precision, F-measure, recall and accuracy; Evaluates the limitations of the proposed research thereby recommending future research.

This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is investigated for compression of Light Field images based on the HEVC technology. A new linear prediction method using sparse constraints is also described, enabling improved coding performance of the HEVC standard, particularly for images with complex textures based on repeated structures. Finally, the authors present a new, generalized intra-prediction framework for the HEVC standard, which unifies the directional prediction methods used in the current video compression standards, with linear prediction methods using sparse constraints. Experimental results for the compression of natural images are provided, demonstrating the advantage of the unified prediction framework over the traditional directional prediction modes used in HEVC standard.

The original concept for the Vision in Vehicle series of international conferences was born from discussions within the Applied Vision Association which led eventually to the first conference being held in 1985. Ten years of progress later and this volume presents the selected and edited proceedings of the Sixth International Conference on Vision in Vehicles (VIV6) which was held at the University of Derby, 13-16 September 1995. The meeting was organised in association with the Applied Vision Association and the Ergonomics Society.
The conference is unique in the eclectic mix of disciplines which are attracted to the meetings and this enables research inssues to be considered in very broad contexts.

The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed monograph studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization.

Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation,
Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets,
Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications,
Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms.

"Scientific Visualization" will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics and those interested in knowing more about the visualization process."

Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness.

This monograph offers a cross-system exchange and cross-modality investigation into brain-heart interplay. Brain-Heart Interplay (BHI) is a highly interdisciplinary scientific topic, which spreads from the physiology of the Central/Autonomous Nervous Systems, especially Central Autonomic Network, to advanced signal processing and modeling for its activity quantification. Motivated by clinical evidence and supported by recent findings in neurophysiology, this monograph first explores the definition of basic Brain-Heart Interplay quantifiers, and then moves onto advanced methods for the assessment of health and disease states. Non-invasive use of brain monitoring techniques, including electroencephalogram and function Magnetic Resonance Imaging, will be described together with heartbeat dynamics monitoring through pulseoximeter and ECG signals. The audience of this book comprises especially of biomedical engineers and medical doctors with expertise in statistics and/or signal processing. Researchers in the fields of cardiology, neurology, psychiatry, and neuroscience in general may be interested as well.

Highlights key research currently being undertaken within the field of telepresence, providing the most detailed account of the field to date, advancing our understanding of a fundamental property of all media - the illusion of presence; the sense of "being there" inside a virtual environment, with actual or virtual others. This collection has been put together by leading international scholars from America, Europe, and Asia. Together, they describe the state-of-the-art in presence theory, research and technology design for an advanced academic audience. Immersed in Media provides research that can help designers optimize presence for users of advanced media technologies such as virtual and augmented reality, collaborative social media, robotics, and artificial intelligence and lead us to better understand human cognition, emotion and behaviour.

This book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time. In concrete terms, future robots will have to solve the classification problem represented by scene recognition sufficiently well for them to act independently in human-centered environments. To achieve accurate yet versatile indoor scene recognition, the book presents a hierarchical data structure for scenes - the Implicit Shape Model trees. Further, it also provides training and recognition algorithms for these trees. In general, entire indoor scenes cannot be perceived from a single point of view. To address this problem the authors introduce Active Scene Recognition (ASR), a concept that embeds canonical scene recognition in a decision-making system that selects camera views for a mobile robot to drive to so that it can find objects not yet localized. The authors formalize the automatic selection of camera views as a Next-Best-View (NBV) problem to which they contribute an algorithmic solution, which focuses on realistic problem modeling while maintaining its computational efficiency. Lastly, the book introduces a method for predicting the poses of objects to be searched, establishing the otherwise missing link between scene recognition and NBV estimation.

This book provides a concise overview of VR systems and their cybersickness effects, giving a description of possible reasons and existing solutions to reduce or avoid them. Moreover, the book explores the impact that understanding how efficiently our brains are producing a coherent and rich representation of the perceived outside world would have on helping VR technics to be more efficient and friendly to use. Getting Rid of Cybersickness will help readers to understand the underlying technics and social stakes involved, from engineering design to autonomous vehicle motion sickness to video games, with the hope of providing an insight of VR sickness induced by the emerging immersive technologies. This book will therefore be of interest to academics, researchers and designers within the field of VR, as well as industrial users of VR and driving simulators.

Visual content understanding is a complex and important challenge for applications in automatic multimedia information indexing, medicine, robotics, and surveillance. Yet the performance of such systems can be improved by the fusion of individual modalities/techniques for content representation and machine learning.

This comprehensive text/reference presents a thorough overview of "Fusion in Computer Vision," from an interdisciplinary and multi-application viewpoint. Presenting contributions from an international selection of experts, the work describes numerous successful approaches, evaluated in the context of international benchmarks that model realistic use cases at significant scales.

Topics and features: examines late fusion approaches for concept recognition in images and videos, including the bag-of-words model; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, for example-based event recognition in video; proposes rotation-based ensemble classifiers for high-dimensional data, which encourage both individual accuracy and diversity within the ensemble; reviews application-focused strategies of fusion in video surveillance, biomedical information retrieval, and content detection in movies; discusses the modeling of mechanisms of human interpretation of complex visual content.

This authoritative collection is essential reading for researchers and students interested in the domain of information fusion for complex visual content understanding, and related fields.

"Progress in Expressive Image Synthesis" (MEIS2015), was held in Fukuoka, Japan, September 25-27, 2015. The aim of the symposium was to provide a unique venue where various issues in computer graphics (CG) application fields could be discussed by mathematicians, CG researchers, and practitioners. Through the previous symposiums MEIS2013 and MEIS2014, mathematicians as well as CG researchers have recognized that CG is a specific and practical activity derived from mathematical theories. Issues found in CG broaden the field of mathematics and vice versa, and CG visualizes mathematical theories in an aesthetic manner. In this volume, the editors aim to provoke interdisciplinary research projects through the peer-reviewed papers and poster presentations at the this year's symposium. This book captures interactions among mathematicians, CG researchers, and practitioners sharing important, state-of-the-art issues in graphics and visual perception. The book is suitable for all CG researchers seeking open problem areas and especially for those entering the field who have not yet selected a research direction.

Computer vision is a rapidly developing and highly interdisciplinary field of computer science and engineering. An increasing number of researchers are turning their attention to the development of vision algorithms that can analyse dynamic images at real-time rates. Real-time vision is needed for automated systems to keep pace with real-world activities and thus control or respond appropriately to them. This is the first book devoted to the subject of real-time computer vision, and includes articles by some of the leading researchers in the world. The focus is on algorithms for interpreting visual input at video rates and on using the gathered information for decision-making and control. Topics covered include: shape recovery; model-based vehicle tracking; active exploration; tracking heads and eyes; controlling robot behavior; visual monitoring; controlling distributed robots. The book will be of interest to students, researchers and engineers involved in the design and programming of visually guided systems.

This book provides a comprehensive introduction to all major topics in digital signal processing (DSP). The book is designed to serve as a textbook for courses offered to undergraduate students enrolled in electrical, electronics, and communication engineering disciplines. The text is augmented with many illustrative examples for easy understanding of the topics covered. Every chapter contains several numerical problems with answers followed by question-and-answer type assignments. The detailed coverage and pedagogical tools make this an ideal textbook for students and researchers enrolled in electrical engineering and related programs.

This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision. Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. Topics and features: discusses in detail three major success stories - the development of the optical mouse, vision for consumer robotics, and vision for automotive safety; reviews state-of-the-art research on embedded 3D vision, UAVs, automotive vision, mobile vision apps, and augmented reality; examines the potential of embedded computer vision in such cutting-edge areas as the Internet of Things, the mining of large data streams, and in computational sensing; describes historical successes, current implementations, and future challenges.

The proceedings includes cutting-edge research articles from the Fourth International Conference on Signal and Image Processing (ICSIP), which is organised by Dr. N.G.P. Institute of Technology, Kalapatti, Coimbatore. The Conference provides academia and industry to discuss and present the latest technological advances and research results in the fields of theoretical, experimental, and application of signal, image and video processing. The book provides latest and most informative content from engineers and scientists in signal, image and video processing from around the world, which will benefit the future research community to work in a more cohesive and collaborative way.

The research and exploitation of optoelectronic properties in the industrial branch of electronics is becoming more popular each day due to the important role they play in the development of a large variety of sensors, devices, and systems for identifying, measuring, and constructing. While optoelectronics study the applications of electronic devices that source, detect, and transform light, machine vision generates and detects light in order to provide imaging-based automatic inspections and analysis for such applications as automatic object and environmental inspection, process control, and robot/mobile machine guidance in industry. Machine vision is less efficient without optoelectronics, and thus, it is important to investigate the theoretical approaches to different optoelectronic devices available for machine vision as well as current scanning technologies. Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications. The book covers topics such as the design, fabrication, and implementation of sensors and devices as well as the development viewpoint of optoelectronic systems and artificial vision techniques using optoelectronic devices. The interaction and informational communication between all these mentioned devices in the complex solution of the same task is the subject of modern challenges in Industry 4.0. Thus, this book supports engineers, technology developers, academicians, researchers, and students who seek machine vision techniques for detection, measurement, and 3D reconstruction.