Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout.

The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year.

This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature.

Describes the operating principles of analog MOS integrated circuits and how to design and use such circuits. The initial section explores general properties of analog MOS integrated circuits and the math and physics background required. The remainder of the book is devoted to the design of circuits. Includes such devices as switched-capacitor filters, analog-to-digital and digital-to-analog converters, amplifiers, modulators, oscillators, and others. Tables and numerical design examples clarify the step-by-step processes involved.

This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI 2019), held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which took place in Shenzhen, China on October 17, 2019. This book presents the latest advances in the rapidly expanding field of diffusion MRI. It shares new perspectives on the latest research challenges for those currently working in the field, but also offers a valuable starting point for anyone interested in learning about computational techniques in diffusion MRI. The book includes rigorous mathematical derivations, a wealth of rich, full-colour visualisations and extensive clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics. Readers will find contributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in vivo recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontline applications in research and clinical practice. This edition includes invited works from high-profile researchers with a specific focus on three new and important topics that are gaining momentum within the diffusion MRI community, including diffusion MRI signal acquisition and processing strategies, machine learning for diffusion MRI, and diffusion MRI outside the brain and clinical applications.

This book analyzes the multimodal verbal and nonverbal behavior of humans in both an artificial game, based on the well-known Mafia and Resistance games, as well as selected other settings. This book develops statistical results linking different types of facial expressions (e.g. smile, pursed lips, raised eyebrows), vocal features (e.g., pitch, loudness) and linguistic features (e.g., dominant language, turn length) with both unary behaviors (e.g. is person X lying?) to binary behaviors (Is person X dominant compared to person Y? Does X trust Y? Does X like Y?). In addition, this book describes machine learning and computer vision-based algorithms that can be used to predict deception, as well as the visual focus of attention of people during discussions that can be linked to many binary behaviors. It is written by a multidisciplinary team of both social scientists and computer scientists. Meetings are at the very heart of human activity. Whether you are involved in a business meeting or in a diplomatic negotiation, such an event has multiple actors, some cooperative and some adversarial. Some actors may be deceptive, others may have complex relationships with others in the group. This book consists of a set of 11 chapters that describe the factors that link human behavior in group settings and attitudes to facial and voice characteristics. Researchers working in social sciences (communication, psychology, cognitive science) with an interest in studying the link between human interpersonal behavior and facial/speech/linguistic characteristics will be interested in this book. Computer scientists, who are interested in developing machine learning and deep learning based models of human behavior in group settings will also be interested in purchasing this book.

This book gathers selected, extended and revised contributions to the 16th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, and the 4th Conference on Imaging and Visualization (CMBBE 2019), held on August 14-16, 2019, in New York City, USA. It reports on cutting-edge models and algorithms for studying various tissues and organs in normal and pathological conditions; innovative imaging and visualization techniques; and the latest diagnostic tools. Further topics addressed include: numerical methods, machine learning approaches, FEM models, and high-resolution imaging and real-time visualization methods applied for biomedical purposes. Given the scope of its coverage, the book provides graduate students and researchers with a timely and insightful snapshot of the latest research and current challenges in biomedical engineering, computational biomechanics and biological imaging, as well as a source of inspiration for future research and cross-disciplinary collaborations.

Fourier Vision provides a new treatment of figure-ground segmentation in scenes comprising transparent, translucent, or opaque objects. Exploiting the relative motion between figure and ground, this technique deals explicitly with the separation of additive signals and makes no assumptions about the spatial or spectral content of the images, with segmentation being carried out phasor by phasor in the Fourier domain. It works with several camera configurations, such as camera motion and short-baseline binocular stereo, and performs best on images with small velocities/displacements, typically one to ten pixels per frame. The book also addresses the use of Fourier techniques to estimate stereo disparity and optical flow. Numerous examples are provided throughout. Fourier Vision will be of value to researchers in image processing & computer vision and, especially, to those who have to deal with superimposed transparent or translucent objects. Researchers in application areas such as medical imaging and acoustic signal processing will also find this of interest.

This book constitutes the refereed proceedings of two International Workshops held as parallel events of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, in Neos Marmaras, Greece, in June 2020: the 9th Mining Humanistic Data Workshop, MHDW 2020, and the 5th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020.* The 6 full papers and 3 short papers presented at MHDW 2020 were carefully reviewed and selected from 16 submissions; out of the 23 papers submitted to 5G-PINE 2020, 11 were accepted as full papers and 1 as a short paper. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and deal with topics such as the Internet of Things, intelligence fusion in 5G networks, and 5G media. *The workshops were held virtually due to the COVID-19 pandemic.

Cardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book includes several prominent imaging modalities, such as MRI, CT and PET technologies. A special emphasis is placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. This is a comprehensive, multi-contributed reference work that details the latest developments in spatial, temporal and functional cardiac imaging.

"Biometrics andKansei Engineering "is the first book to bring together the principles and applications of each discipline. The future of biometrics is in need of new technologies that can depend on people's emotions and the prediction of their intention to take an action. Behavioral biometrics studies the way people walk, talk, and express their emotions, and Kansei Engineering focuses on interactions between users, products/services and product psychology. They are becoming quite complementary.

This book also introduces biometric applications in our environment, which further illustrates the close relationship between Biometrics and Kansei Engineering. Examples and case studies are provided throughout this book.

"Biometrics and Kansei Engineering "is designed as a reference book for professionals working in these related fields. Advanced-level students and researchers studying computer science and engineering will find this book useful as a reference or secondary text book as well. "

This book presents revised versions of the best papers selected from the symposium Mathematical Progress in Expressive Image Synthesis (MEIS2013) held in Fukuoka, Japan, in 2013. The topics cover various areas of computer graphics (CG), such as surface deformation/editing, character animation, visual simulation of fluids, texture and sound synthesis and photorealistic rendering. From a mathematical point of view, the book also presents papers addressing discrete differential geometry, Lie theory, computational fluid dynamics, function interpolation and learning theory. This book showcases the latest joint efforts between mathematicians, CG researchers and practitioners exploring important issues in graphics and visual perception.The book provides a valuable resource for all computer graphics researchers seeking open problem areas, especially those now entering the field who have not yet selected a research direction."

Computer vision falls short of human vision in two respects: execution time and intelligent interpretation. This book addresses the question of execution time. It is based on a workshop on specialized processors for real-time image analysis, held as part of the activities of an ESPRIT Basic Research Action, the Working Group on Vision. The aim of the book is to examine the state of the art in vision-oriented computers. Two approaches are distinguished: multiprocessor systems and fine-grain massively parallel computers. The development of fine-grain machines has become more important over the last decade, but one of the main conclusions of the workshop is that this does not imply the replacement of multiprocessor machines. The book is divided into four parts. Part 1 introduces different architectures for vision: associative and pyramid processors as examples of fine-grain machines and a workstation with bus-oriented network topology as an example of a multiprocessor system. Parts 2 and 3 deal with the design and development of dedicated and specialized architectures. Part 4 is mainly devoted to applications, including road segmentation, mobile robot guidance and navigation, reconstruction and identification of 3D objects, and motion estimation.

Semantic Video Object Segmentation for Content-Based Multimedia Applications provides a thorough review of state-of-the-art techniques as well as describing several novel ideas and algorithms for semantic object extraction from image sequences. Semantic object extraction is an essential element in content-based multimedia services, such as the newly developed MPEG4 and MPEG7 standards. An interactive system called SIVOG (Smart Interactive Video Object Generation) is presented, which converts user's semantic input into a form that can be conveniently integrated with low-level video processing. Thus, high-level semantic information and low-level video features are integrated seamlessly into a smart segmentation system. A region and temporal adaptive algorithm was further proposed to improve the efficiency of the SIVOG system so that it is feasible to achieve nearly real-time video object segmentation with robust and accurate performances. Also included is an examination of the shape coding problem and the object segmentation problem simultaneously. Semantic Video Object Segmentation for Content-Based Multimedia Applications will be of great interest to research scientists and graduate-level students working in the area of content-based multimedia representation and applications and its related fields.

This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.

fMRI Neurofeedback provides a perspective on how the field of functional magnetic resonance imaging (fMRI) neurofeedback has evolved, an introduction to state-of-the-art methods used for fMRI neurofeedback, a review of published neuroscientific and clinical applications, and a discussion of relevant ethical considerations. It gives a view of the ongoing research challenges throughout and provides guidance for researchers new to the field on the practical implementation and design of fMRI neurofeedback protocols. This book is designed to be accessible to all scientists and clinicians interested in conducting fMRI neurofeedback research, addressing the variety of different knowledge gaps that readers may have given their varied backgrounds and avoiding field-specific jargon. The book, therefore, will be suitable for engineers, computer scientists, neuroscientists, psychologists, and physicians working in fMRI neurofeedback.

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

Inverse problems such as imaging or parameter identification deal with the recovery of unknown quantities from indirect observations, connected via a model describing the underlying context. While traditionally inverse problems are formulated and investigated in a static setting, we observe a significant increase of interest in time-dependence in a growing number of important applications over the last few years. Here, time-dependence affects a) the unknown function to be recovered and / or b) the observed data and / or c) the underlying process. Challenging applications in the field of imaging and parameter identification are techniques such as photoacoustic tomography, elastography, dynamic computerized or emission tomography, dynamic magnetic resonance imaging, super-resolution in image sequences and videos, health monitoring of elastic structures, optical flow problems or magnetic particle imaging to name only a few. Such problems demand for innovation concerning their mathematical description and analysis as well as computational approaches for their solution.

1) Learn how to develop computer vision application algorithms 2) Learn to use software tools for analysis and development 3) Learn underlying processes need for image analysis 4) Learn concepts so that the reader can develop their own algorithms 5) Software tools provided

This book provides insights into the state of the art of digital cultural heritage using computer graphics, image processing, computer vision, visualization and reconstruction, virtual and augmented reality and serious games. It aims at covering the emergent approaches for digitization and preservation of Cultural Heritage, both in its tangible and intangible facets. Advancements in Digital Cultural Heritage research have been abundant in recent years covering a wide assortment of topics, ranging from visual data acquisition, pre-processing, classification, analysis and synthesis, 3D modelling and reconstruction, semantics and symbolic representation, metadata description, repository and archiving, to new forms of interactive and personalized presentation, visualization and immersive experience provision via advanced computer graphics, interactive virtual and augmented environments, serious games and digital storytelling. Different aspects pertaining to visual computing with regard to tangible (books, images, paintings, manuscripts, uniforms, maps, artefacts, archaeological sites, monuments) and intangible (e.g. dance and performing arts, folklore, theatrical performances) cultural heritage preservation, documentation, protection and promotion are covered, including rendering and procedural modelling of cultural heritage assets, keyword spotting in old documents, drone mapping and airborne photogrammetry, underwater recording and reconstruction, gamification, visitor engagement, animated storytelling, analysis of choreographic patterns, and many more. The book brings together and targets researchers from the domains of computing, engineering, archaeology and the arts, and aims at underscoring the potential for cross-fertilization and collaboration among these communities.

This book provides readers with a comprehensive review of image quality assessment technology, particularly applications on screen content images, 3D-synthesized images, sonar images, enhanced images, light-field images, VR images, and super-resolution images. It covers topics containing structural variation analysis, sparse reference information, multiscale natural scene statistical analysis, task and visual perception, contour degradation measurement, spatial angular measurement, local and global assessment metrics, and more. All of the image quality assessment algorithms of this book have a high efficiency with better performance compared to other image quality assessment algorithms, and the performance of these approaches mentioned above can be demonstrated by the results of experiments on real-world images. On the basis of this, those interested in relevant fields can use the results obtained through these quality assessment algorithms for further image processing. The goal of this book is to facilitate the use of these image quality assessment algorithms by engineers and scientists from various disciplines, such as optics, electronics, math, photography techniques and computation techniques. The book can serve as a reference for graduate students who are interested in image quality assessment techniques, for front-line researchers practicing these methods, and for domain experts working in this area or conducting related application development.

This book addresses and disseminates research and development in the applications of intelligent techniques for computer vision, the field that works on enabling computers to see, identify, and process images in the same way that human vision does, and then providing appropriate output. The book provides contributions which include theory, case studies, and intelligent techniques pertaining to computer vision applications. The book helps readers grasp the essence of the recent advances in this complex field. The audience includes researchers, professionals, practitioners, and students from academia and industry who work in this interdisciplinary field. The authors aim to inspire future research both from theoretical and practical viewpoints to spur further advances in the field.

This book explains how depth measurements from the Time-of-Flight (ToF) range imaging cameras are influenced by the electronic timing-jitter. The author presents jitter extraction and measurement techniques for any type of ToF range imaging cameras. The author mainly focuses on ToF cameras that are based on the amplitude modulated continuous wave (AMCW) lidar techniques that measure the phase difference between the emitted and reflected light signals. The book discusses timing-jitter in the emitted light signal, which is sensible since the light signal of the camera is relatively straightforward to access. The specific types of jitter that present on the light source signal are investigated throughout the book. The book is structured across three main sections: a brief literature review, jitter measurement, and jitter influence in AMCW ToF range imaging.

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

This book presents the interdisciplinary and international "Virtual and Remote Tower" research and development work. It has been carried out since nearly twenty years with the goal of replacing the conventional aerodrome control tower by a new "Remote Tower Operation" (RTO) work environment for enhancing work efficiency and safety and reducing cost. The revolutionary human-system interface replaces the out-of-windows view by an augmented vision video panorama that allows for remote aerodrome traffic control without a physical tower building. It enables the establishment of a (multiple) remote control center (MRTO, RTC) that may serve several airports from a central location. The first (2016) edition of this book covered all aspects from preconditions over basic research and prototype development to initial validation experiments with field testing. Co-edited and -authored by DLR RTO-team members Dr. Anne Papenfuss and Joern Jakobi, this second extended edition with nearly doubled number of chapters includes further important aspects of the international follow-up work towards the RTO-deployment. Focus of the extension with new contributions from ENRI/Japan and IAA/Dublin with Cranfield University, is on MRTO, workload, implementation, and standardization. Specifically, the two revised and nine new Chapters put the focus on inclusion of augmented vision and virtual reality technologies, human-in-the-loop simulation for quantifying workload and deriving minimum (technical) requirements according to standards of the European Organization for Civil Aviation Equipment (EUROCAE), and MRTO implementation and certification. Basics of optical / video design, workload measures, and advanced psychophysical data analysis are presented in four appendices.

This book presents novel hybrid encryption algorithms that possess many different characteristics. In particular, "Hybrid Encryption Algorithms over Wireless Communication Channels", examines encrypted image and video data for the purpose of secure wireless communications. A study of two different families of encryption schemes are introduced: namely, permutation-based and diffusion-based schemes. The objective of the book is to help the reader selecting the best suited scheme for the transmission of encrypted images and videos over wireless communications channels, with the aid of encryption and decryption quality metrics. This is achieved by applying number-theory based encryption algorithms, such as chaotic theory with different modes of operations, the Advanced Encryption Standard (AES), and the RC6 in a pre-processing step in order to achieve the required permutation and diffusion. The Rubik's cube is used afterwards in order to maximize the number of permutations. Transmission of images and videos is vital in today's communications systems. Hence, an effective encryption and modulation schemes are a must. The author adopts Orthogonal Frequency Division Multiplexing (OFDM), as the multicarrier transmission choice for wideband communications. For completeness, the author addresses the sensitivity of the encrypted data to the wireless channel impairments, and the effect of channel equalization on the received images and videos quality. Complete simulation experiments with MATLAB (R) codes are included. The book will help the reader obtain the required understanding for selecting the suitable encryption method that best fulfills the application requirements.