The research book is a continuation of the authors' previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

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 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.

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role.
This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication.
Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field.
Key Features
* This state-of-the-art book brings together selected review articles and accounts of current projects from world-renowned researchers at the forefront of this exciting area; The contributions cover topics such as:
* psychology of perception
* image processing
* computational geometry
* visual knowledge representation and languages
* It is this truly multi-disciplinary approach that has produced successful theories and applications for the subject.

This book focuses on the generalization of map features, providing descriptions and classifying groups of map objects into six categories: point clusters, groups of contours, road networks, river networks, continuous areal features and discrete areal features. Discussing the methods and algorithms in map generalization in equal measure, it also describes the approaches for describing map features. The book is a valuable reference for graduates and researchers who are interested in cartography and geographic information science/systems, especially those in automated map generalization and spatial databases construction.

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 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.

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 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.

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.

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.

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.

Computer vision is an interdisciplinary scientific field that deals with how computers obtain, store, interpret and understand digital images or videos using artificial intelligence based on neural networks, machine learning and deep learning methodologies. They are used in countless applications such as image retrieval and classification, driving and transport monitoring, medical diagnostics and aerial monitoring. Written by a team of international experts, this edited book covers the state-of-the-art of advanced research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real world applications including object detection, biometrics, Deepfake detection, sentiment and emotion analysis, traffic enforcement camera monitoring, vehicle control and aerial remote sensing imagery. The book will be useful for industry and academic researchers, scientists and engineers in the fields of computer vision, machine vision, image processing and recognition, multimedia, AI, machine and deep learning, data science, biometrics, security, and signal processing. It will also make a great course reference for advanced students and lecturers in these fields of research.

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.

This book presents a comprehensive study of different tools and techniques available to perform network forensics. Also, various aspects of network forensics are reviewed as well as related technologies and their limitations. This helps security practitioners and researchers in better understanding of the problem, current solution space, and future research scope to detect and investigate various network intrusions against such attacks efficiently. Forensic computing is rapidly gaining importance since the amount of crime involving digital systems is steadily increasing. Furthermore, the area is still underdeveloped and poses many technical and legal challenges. The rapid development of the Internet over the past decade appeared to have facilitated an increase in the incidents of online attacks. There are many reasons which are motivating the attackers to be fearless in carrying out the attacks. For example, the speed with which an attack can be carried out, the anonymity provided by the medium, nature of medium where digital information is stolen without actually removing it, increased availability of potential victims and the global impact of the attacks are some of the aspects. Forensic analysis is performed at two different levels: Computer Forensics and Network Forensics. Computer forensics deals with the collection and analysis of data from computer systems, networks, communication streams and storage media in a manner admissible in a court of law. Network forensics deals with the capture, recording or analysis of network events in order to discover evidential information about the source of security attacks in a court of law. Network forensics is not another term for network security. It is an extended phase of network security as the data for forensic analysis are collected from security products like firewalls and intrusion detection systems. The results of this data analysis are utilized for investigating the attacks. Network forensics generally refers to the collection and analysis of network data such as network traffic, firewall logs, IDS logs, etc. Technically, it is a member of the already-existing and expanding the field of digital forensics. Analogously, network forensics is defined as "The use of scientifically proved techniques to collect, fuses, identifies, examine, correlate, analyze, and document digital evidence from multiple, actively processing and transmitting digital sources for the purpose of uncovering facts related to the planned intent, or measured success of unauthorized activities meant to disrupt, corrupt, and or compromise system components as well as providing information to assist in response to or recovery from these activities." Network forensics plays a significant role in the security of today's organizations. On the one hand, it helps to learn the details of external attacks ensuring similar future attacks are thwarted. Additionally, network forensics is essential for investigating insiders' abuses that constitute the second costliest type of attack within organizations. Finally, law enforcement requires network forensics for crimes in which a computer or digital system is either being the target of a crime or being used as a tool in carrying a crime. Network security protects the system against attack while network forensics focuses on recording evidence of the attack. Network security products are generalized and look for possible harmful behaviors. This monitoring is a continuous process and is performed all through the day. However, network forensics involves post mortem investigation of the attack and is initiated after crime notification. There are many tools which assist in capturing data transferred over the networks so that an attack or the malicious intent of the intrusions may be investigated. Similarly, various network forensic frameworks are proposed in the literature.

The author defines "Geometric Algebra Computing" as the geometrically intuitive development of algorithms using geometric algebra with a focus on their efficient implementation, and the goal of this book is to lay the foundations for the widespread use of geometric algebra as a powerful, intuitive mathematical language for engineering applications in academia and industry. The related technology is driven by the invention of conformal geometric algebra as a 5D extension of the 4D projective geometric algebra and by the recent progress in parallel processing, and with the specific conformal geometric algebra there is a growing community in recent years applying geometric algebra to applications in computer vision, computer graphics, and robotics. This book is organized into three parts: in Part I the author focuses on the mathematical foundations; in Part II he explains the interactive handling of geometric algebra; and in Part III he deals with computing technology for high-performance implementations based on geometric algebra as a domain-specific language in standard programming languages such as C++ and OpenCL. The book is written in a tutorial style and readers should gain experience with the associated freely available software packages and applications. The book is suitable for students, engineers, and researchers in computer science, computational engineering, and mathematics.

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.

"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.

This book contains the full papers presented at the MICCAI 2013 workshop Bio-Imaging and Visualization for Patient-Customized Simulations (MWBIVPCS 2013). MWBIVPCS 2013 brought together researchers representing several fields, such as Biomechanics, Engineering, Medicine, Mathematics, Physics and Statistic.

The contributions included in this book present and discuss new trends in those fields, using several methods and techniques, including the finite element method, similarity metrics, optimization processes, graphs, hidden Markov models, sensor calibration, fuzzy logic, data mining, cellular automation, active shape models, template matching and level sets. These serve as tools to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modelling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis.

This book will appeal to researchers, PhD students and graduate students with multidisciplinary interests related to the areas of medical imaging, image processing and analysis, computer vision, image segmentation, image registration and fusion, scientific data visualization and image based modeling and simulation.

This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently proposed signal processing tools and methods for addressing biological signals is included. The target audience primarily comprises researchers and expert practitioners but the book may also be beneficial for graduate students.

Some of the fundamental constraints of automated machine vision have been the inability to automatically adapt parameter settings or utilize previous adaptations in changing environments. Symbolic Visual Learning presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Written as a companion volume to Early Visual Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning.

Business and medical professionals rely on large data sets to identify trends or other knowledge that can be gleaned from the collection of it. New technologies concentrate on data's management, but do not facilitate users' extraction of meaningful outcomes. Pattern and Data Analysis in Healthcare Settings investigates the approaches to shift computing from analysis on-demand to knowledge on-demand. By providing innovative tactics to apply data and pattern analysis, these practices are optimized into pragmatic sources of knowledge for healthcare professionals. This publication is an exhaustive source for policy makers, developers, business professionals, healthcare providers, and graduate students concerned with data retrieval and analysis.

This book introduces the optical multi-band polarization imaging theory and the utilization of the multi-band polarimetric information for detecting the camouflage object and the optical hidden marker, and enhancing the visibility in bad weather and water. The book describes systematically and in detail the basic optical polarimetry theory; provides abundant multi-band polarimetric imaging experiment data; and indicates practical evaluation methods for designing the multi-band polarization imager, for analyzing and modeling the object's multi-band polarization characteristics, and for enhancing the vision performance in scattering media. This book shows the latest research results of multi-band polarimetric vision, especially in camouflage object detection, optical hidden marker detection and multi-band polarimetric imagery fusion. From this book, readers can get a complete understanding about multi-band polarimetric imaging and its application in different vision tasks.