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The textbook is primarily written for senior undergraduate and post graduate students studying in areas of computer science and engineering, and electrical engineering. However, as the subject covers various interdisciplinary areas, the book is also expected to be of interest to a larger readership in Science and Engineering. It has a comprehensive and balanced coverage of theory and applications of computer vision with a textbook approach providing worked out examples, and exercises. It covers theory and applications of some relatively recent advancements in technology such as on colour processing, deep learning techniques for processing images and videos, document processing, biometry, content based image retrieval, etc. It also delves with theories and processing in non-optical imaging systems, such as range or depth imaging, medical imaging and remote sensing imaging.
This book applies rotation theory to problems involving vectors and coordinates, with an approach that combines easily visualised procedures with smart mathematics. It constructs rotation theory from the ground up, building from basic geometry through to the motion and attitude equations of rockets, and the tensor analysis of relativity. The author replaces complicated pictures of superimposed axes with a simple and intuitive procedure of rotating a model aircraft, to create rotation sequences that are easily turned into mathematics. He combines the best of the 'active' and 'passive' approaches to rotation into a single coherent theory, and discusses many potential traps for newcomers. This volume will be useful to astronomers and engineers sighting planets and satellites, computer scientists creating graphics for movies, and aerospace engineers designing aircraft; also to physicists and mathematicians who study its abstract aspects.
This innovative introduction to the foundations of signals, systems, and transforms emphasises discrete-time concepts, smoothing the transition towards more advanced study in Digital Signal Processing (DSP). A digital-first approach, introducing discrete-time concepts from the beginning, equips students with a firm theoretical foundation in signals and systems, while emphasising topics fundamental to understanding DSP. Continuous-time approaches are introduced in later chapters, providing students with a well-rounded understanding that maintains a strong digital emphasis. Real-world applications, including music signals, signal denoising systems, and digital communication systems, are introduced to encourage student motivation. Early introduction of core concepts in digital filtering, DFT and FFT provide a frictionless transition through to more advanced study. Over 325 end-of-chapter problems, and over 50 computational problems using Matlab. Accompanied online by solutions and code for instructors, this rigorous textbook is ideal for undergraduate students in electrical engineering studying an introductory course in signals, systems, and signal processing.
The role of robots in society keeps expanding and diversifying, bringing with it a host of issues surrounding the relationship between robots and humans. This introduction to human–robot interaction (HRI) by leading researchers in this developing field is the first to provide a broad overview of the multidisciplinary topics central to modern HRI research. Written for students and researchers from robotics, artificial intelligence, psychology, sociology, and design, it presents the basics of how robots work, how to design them, and how to evaluate their performance. Self-contained chapters discuss a wide range of topics, including speech and language, nonverbal communication, and processing emotions, plus an array of applications and the ethical issues surrounding them. This revised and expanded second edition includes a new chapter on how people perceive robots, coverage of recent developments in robotic hardware, software, and artificial intelligence, and exercises for readers to test their knowledge.
This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots. Ideal for self-learning, or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background. Modern Robotics presents the state-of-the-art, screw-theoretic techniques capturing the most salient physical features of a robot in an intuitive geometrical way. With numerous exercises at the end of each chapter, accompanying software written to reinforce the concepts in the book and video lectures aimed at changing the classroom experience, this is the go-to textbook for learning about this fascinating subject.
Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary field of mobile robotics, which lies at the intersection of artificial intelligence, computational vision, and traditional robotics. Written for advanced undergraduates and graduate students in computer science and engineering, the book covers algorithms for a range of strategies for locomotion, sensing, and reasoning. The new edition includes recent advances in robotics and intelligent machines, including coverage of human-robot interaction, robot ethics, and the application of advanced AI techniques to end-to-end robot control and specific computational tasks. This book also provides support for a number of algorithms using ROS 2, and includes a review of critical mathematical material and an extensive list of sample problems. Researchers as well as students in the field of mobile robotics will appreciate this comprehensive treatment of state-of-the-art methods and key technologies.
A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Kalman filter) but also important modern topics such as batch estimation, Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. Since most robots operate in a three-dimensional world, common sensor models (e.g., camera, laser rangefinder) are provided followed by practical advice on how to carry out state estimation for rotational state variables. The book covers robotic applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Highlights of this expanded second edition include a new chapter on variational inference, a new section on inertial navigation, more introductory material on probability, and a primer on matrix calculus.
Virtual reality (VR) is a powerful technology that promises to transform our lives. This balanced and interdisciplinary text blends the key components from computer graphics, perceptual psychology, human physiology, behavioral science, media studies, human-computer interaction, optical engineering, and sensing and filtering, showing how each contributes to engineering perceptual illusions. Steven LaValle draws on his unique experience as a teacher, researcher, and early founder of Oculus VR, to demonstrate how the best practices and insights from industry are built on fundamental computer science principles. Topics include media history, geometric modeling, optical systems, displays, eyes, ears, low-level perception, neuroscience of vision, graphical rendering, tracking systems, interaction mechanisms, audio, evaluating VR systems, and mitigating side effects. Students, researchers, and developers will gain a clear understanding of timeless foundations and new applications, enabling them to make innovative contributions to this growing field as scientists, engineers, business developers, and content makers.
Projective geometry is the geometry of vision, and this book introduces students to this beautiful subject from an analytic perspective, emphasising its close relationship with linear algebra and the central role of symmetry. Starting with elementary and familiar geometry over real numbers, readers will soon build upon that knowledge via geometric pathways and journey on to deep and interesting corners of the subject. Through a projective approach to geometry, readers will discover connections between seemingly distant (and ancient) results in Euclidean geometry. By mixing recent results from the past 100 years with the history of the field, this text is one of the most comprehensive surveys of the subject and an invaluable reference for undergraduate and beginning graduate students learning classic geometry, as well as young researchers in computer graphics. Students will also appreciate the worked examples and diagrams throughout.
How can we provide guarantees of behaviours for autonomous systems such as driverless cars? This tutorial text, for professionals, researchers and graduate students, explains how autonomous systems, from intelligent robots to driverless cars, can be programmed in ways that make them amenable to formal verification. The authors review specific definitions, applications and the unique future potential of autonomous systems, along with their impact on safer decisions and ethical behaviour. Topics discussed include the use of rational cognitive agent programming from the Beliefs-Desires-Intentions paradigm to control autonomous systems and the role model-checking in verifying the properties of this decision-making component. Several case studies concerning both the verification of autonomous systems and extensions to the framework beyond the model-checking of agent decision-makers are included, along with complete tutorials for the use of the freely-available verifiable cognitive agent toolkit Gwendolen, written in Java.
Discover a fresh take on classical screw theory and understand the geometry embedded within robots and mechanisms with this essential text. The book begins with a geometrical study of points, lines, and planes and slowly takes the reader toward a mastery of screw theory with some cutting-edge results, all while using only basic linear algebra and ordinary vectors. It features a discussion of the geometry of parallel and serial robot manipulators, in addition to the reciprocity of screws and a singularity study. All 41 essential screw systems are unveiled, establishing the possible freedom twists and constraint wrenches for a kinematic joint. Familiarizing the reader with screw geometry in order to study the statics and kinematics of robots and mechanisms, this is a perfect resource for engineers and graduate students.
This collection considers new phenomena emerging in a convergence environment from the perspective of adaptation studies. The contributions take the most prominent methods within the field to offer reconsiderations of theoretical concepts and practices in participatory culture, transmedia franchises, and new media adaptations. The authors discuss phenomena ranging from mash-ups of novels and YouTube cover songs to negotiations of authorial control and interpretative authority between media producers and fan communities to perspectives on the fictional and legal framework of brands and franchises. In this fashion, the collection expands the horizons of both adaptation and transmedia studies and provides reassessments of frequently discussed (BBC’s Sherlock or the LEGO franchise) and previously largely ignored phenomena (self-censorship in transnational franchises, mash-up novels, or YouTube cover videos).
The role of robots in society keeps expanding and diversifying, bringing with it a host of issues surrounding the relationship between robots and humans. This introduction to human-robot interaction (HRI), written by leading researchers in this developing field, is the first to provide a broad overview of the multidisciplinary topics central to modern HRI research. Students and researchers from robotics, artificial intelligence, psychology, sociology, and design will find it a concise and accessible guide to the current state of the field. Written for students from diverse backgrounds, it presents relevant background concepts, describing how robots work, how to design them, and how to evaluate their performance. Self-contained chapters discuss a wide range of topics, including the different communication modalities such as speech and language, non-verbal communication and the processing of emotions, as well as ethical issues around the application of robots today and in the context of our future society.
Humans are the best functioning example of multimedia communication and computing - that is, we understand information and experiences through the unified perspective offered by our five senses. This innovative textbook presents emerging techniques in multimedia computing from an experiential perspective in which each medium - audio, images, text, and so on - is a strong component of the complete, integrated exchange of information or experience. The authors' goal is to present current techniques in computing and communication that will lead to the development of a unified and holistic approach to computing using heterogeneous data sources. Gerald Friedland and Ramesh Jain introduce the fundamentals of multimedia computing, describing the properties of perceptually encoded information, presenting common algorithms and concepts for handling it, and outlining the typical requirements for emerging applications that use multifarious information sources. Designed for advanced undergraduate and beginning graduate courses, the book will also serve as an introduction for engineers and researchers interested in understanding the elements of multimedia and their role in building specific applications.
An authoritative exposition of the methods at the heart of modern non-stationary signal processing from a recognised leader in the field. Offering a global view that favours interpretations and historical perspectives, it explores the basic concepts of time-frequency analysis, and examines the most recent results and developments in the field in the context of existing, lesser-known approaches. Several example waveform families from bioacoustics, mathematics and physics are examined in detail, with the methods for their analysis explained using a wealth of illustrative examples. Methods are discussed in terms of analysis, geometry and statistics. This is an excellent resource for anyone wanting to understand the 'why and how' of important methodological developments in time-frequency analysis, including academics and graduate students in signal processing and applied mathematics, as well as application-oriented scientists.
This self-contained, systematic treatment of multivariate approximation begins with classical linear approximation, and moves on to contemporary nonlinear approximation. It covers substantial new developments in the linear approximation theory of classes with mixed smoothness, and shows how it is directly related to deep problems in other areas of mathematics. For example, numerical integration of these classes is closely related to discrepancy theory and to nonlinear approximation with respect to special redundant dictionaries, and estimates of the entropy numbers of classes with mixed smoothness are closely related to (in some cases equivalent to) the Small Ball Problem from probability theory. The useful background material included in the book makes it accessible to graduate students. Researchers will find that the many open problems in the theory outlined in the book provide helpful directions and guidance for their own research in this exciting and active area.
This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.
Get to grips with the principles and practice of signal processing used in mobile communications systems. Focusing particularly on speech, video, and modem signal processing, pioneering experts employ a detailed, top-down analytical approach to outline the network architectures and protocol structures of multiple generations of mobile communications systems, identify the logical ranges where media and radio signal processing occur, and analyze the procedures for capturing, compressing, transmitting, and presenting media. Chapters are uniquely structured to show the evolution of network architectures and technical elements between generations up to and including 5G, with an emphasis on maximizing service quality and network capacity through re-using existing infrastructure and technologies. Implementation examples and data taken from commercial networks provide an in-depth insight into the operation of real mobile communications systems, including GSM, cdma2000, W-CDMA, LTE, and LTE-A, making this a practical, hands-on guide for both practicing engineers and graduate students in wireless communications.
Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mathematical and algorithmic tools to develop a thorough understanding of the underlying components of any complete computer vision system and to design such systems. These components include identifying local features such as corners or edges in the presence of noise, edge preserving smoothing, connected component labeling, stereopsis, thresholding, clustering, segmentation, and describing and matching both shapes and scenes. The extensive examples include photographs of faces, cartoons, animal footprints, and angiograms, and each chapter concludes with homework exercises and suggested projects. Intended for advanced undergraduate and beginning graduate students, the text will also be of use to practitioners and researchers in a range of applications.
A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents common sensor models and practical advice on how to carry out state estimation for rotations and other state variables. It covers both classical state estimation methods such as the Kalman filter, as well as important modern topics such as batch estimation, the Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. The methods are demonstrated in the context of important applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Students and practitioners of robotics alike will find this a valuable resource.
