Computer Vision

This is the first book which informs about recent progress in biomechanics, computer vision and computer graphics – all in one volume. Researchers from these areas have contributed to this book to pro

Bayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. This 1996 book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modelling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.

Stars form surrounded by a circumstellar disk which is thought to be the cradle of planets. IAU Symposium 243 highlights the latest developments in understanding the structure and evolution of the star-disk interaction region in young stars, a critical component of our knowledge of star and planetary system formation processes. Discussions review the physical processes thought to be at work at the star-disk interface, confront the predictions of the latest numerical and analytical magnetohydrodynamic models of star-disk-jet systems with observations, and explore the consequences of these processes for stellar angular momentum evolution and inner disk structure. The most recent observational results, computer simulations and theoretical developments in this active field of research are included to provide a unique vision into this central aspect of the star and planet formation problem.

This richly illustrated book introduces the reader to a newly developed theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are inspired by, and are a

There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and sh

This book provides an introduction to the use of geometric partial differential equations in image processing and computer vision. This research area brings a number of new concepts into the field, providing a very fundamental and formal approach to image processing. State-of-the-art practical results in a large number of real problems are achieved with the techniques described in this book. Applications covered include image segmentation, shape analysis, image enhancement, and tracking. This book will be a useful resource for researchers and practitioners. It is intended to provide information for people investigating new solutions to image processing problems as well as for people searching for existent advanced solutions.

dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision. This le

The book is intended for advanced students in physics, mathematics, computer science, electrical engineering, robotics, engine engineering and for specialists in computer vision and robotics on the te

Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then compu

Chan (mathematics, University of California) and Shen (mathematics, University of Minnesota) develop the mathematical foundations of modern image processing and low-level computer vision. They first i

This book offers an in-depth introduction to video-based rendering (VBR), a rapidly developing interdisciplinary topic employing techniques from computer graphics, computer vision, and telecommunicat

Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilat

Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and

An understanding of random processes is crucial to many engineering fields-including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vi

Felix Klein, one of the great nineteenth-century geometers, discovered in mathematics an idea prefigured in Buddhist mythology: the heaven of Indra contained a net of pearls, each of which was reflected in its neighbour, so that the whole Universe was mirrored in each pearl. Klein studied infinitely repeated reflections and was led to forms with multiple coexisting symmetries. For a century, these images barely existed outside the imagination of mathematicians. However, in the 1980s, the authors embarked on the first computer exploration of Klein's vision, and in doing so found many further extraordinary images. Join the authors on the path from basic mathematical ideas to the simple algorithms that create the delicate fractal filigrees, most of which have never appeared in print before. Beginners can follow the step-by-step instructions for writing programs that generate the images. Others can see how the images relate to ideas at the forefront of research.

This book begins with a promise: people with severe vision loss can be trained and equipped to function as sighted. The author, himself legally blind for 30 years, fulfills that promise with precise information and guidance on improving life through visual rehabilitation. The book explains fundamental facts about eyes and vision, including the causes and varieties of blindness, and then moves on to the new skills the partially sighted person must learn. Specific approaches and devices are covered in depth, including “eccentric viewing” and driving with telescopic glasses, and the visual and electronic aids that can help overcome the effects of vision loss. In spite of his own limited vision (20/240), Dr. Chapman uses a computer without a voice synthesizer, watches TV, and even drives, and he shows readers how to do the same.

A representation of objects by their parts is the dominant strategy for representing complex 3D objects in many disciplines. In computer vision and robotics, superquadrics are among the most widesprea

Computer vision aims to detect and reconstruct features of surfaces from the images produced by cameras, in some way mimicking the way in which humans reconstruct features of the world around them by using their eyes. In this book the authors describe research in computer vision aimed at recovering the 3D shape of surfaces from image sequences of their 'outlines'. They provide all the necessary background in differential geometry (assuming knowledge of elementary algebra and calculus) and in the analysis of visual motion, emphasising intuitive visual understanding of the geometric techniques with computer-generated illustrations. They also give a thorough introduction to the mathematical techniques and the details of the implementations and apply the methods to data from real images using the most current techniques.

Computer whiz Ashley Patterson is convinced she is being stalked. Coworker Toni Prescott has a penchant for Internet dating and little time for anyone else. And Alette Peters prefers quiet weekends in

Singularity theory is a broad subject with vague boundaries. It draws on many other areas of mathematics, and in turn has contributed to many areas both within and outside mathematics, in particular differential and algebraic geometry, knot theory, differential equations, bifurcation theory, Hamiltonian mechanics, optics, robotics and computer vision. This volume consists of two dozen articles from some of the best known figures in singularity theory, and it presents an up-to-date survey of research in this area.

This new edition of Professor Sethian's successful text provides an introduction to level set methods and fast marching methods, which are powerful numerical techniques for analyzing and computing interface motion in a host of settings. They rely on a fundamental shift in how one views moving boundaries; rethinking the natural geometric Lagrangian perspective and exchanging it for an Eulerian, initial value partial differential equation perspective. For this edition, the collection of applications provided in the text has been expanded, including examples from physics, chemistry, fluid mechanics, combustion, image processing, material science, fabrication of microelectronic components, computer vision, computer-aided design, and optimal control theory. This book will be a useful resource for mathematicians, applied scientists, practising engineers, computer graphic artists, and anyone interested in the evolution of boundaries and interfaces.

There has been a resurgence of interest in classical invariant theory driven by several factors: new theoretical developments; a revival of computational methods coupled with powerful new computer algebra packages; and a wealth of new applications, ranging from number theory to geometry, physics to computer vision. This book provides readers with a self-contained introduction to the classical theory as well as modern developments and applications. The text concentrates on the study of binary forms (polynomials) in characteristic zero, and uses analytical as well as algebraic tools to study and classify invariants, symmetry, equivalence and canonical forms. It also includes a variety of innovations that make this text of interest even to veterans of the subject. Aimed at advanced undergraduate and graduate students the book includes many exercises and historical details, complete proofs of the fundamental theorems, and a lively and provocative exposition.

There has been a resurgence of interest in classical invariant theory driven by several factors: new theoretical developments; a revival of computational methods coupled with powerful new computer algebra packages; and a wealth of new applications, ranging from number theory to geometry, physics to computer vision. This book provides readers with a self-contained introduction to the classical theory as well as modern developments and applications. The text concentrates on the study of binary forms (polynomials) in characteristic zero, and uses analytical as well as algebraic tools to study and classify invariants, symmetry, equivalence and canonical forms. It also includes a variety of innovations that make this text of interest even to veterans of the subject. Aimed at advanced undergraduate and graduate students the book includes many exercises and historical details, complete proofs of the fundamental theorems, and a lively and provocative exposition.

Charles Babbage, "the grandfather of the modern computer," did not live to see even one of his calculating machines at work. A dazzling genius with vision extending far beyond the limitations of the V

This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two gen

The design and analysis of geometric algorithms have seen remarkable growth in recent years, due to their application in, for example, computer vision, graphics, medical imaging and CAD. The goals of this book are twofold: first to provide a coherent and systematic treatment of the foundations; secondly to present algorithmic solutions that are amenable to rigorous analysis and are efficient in practical situations. When possible, the algorithms are presented in their most general d-dimensional setting. Specific developments are given for the 2- or 3-dimensional cases when this results in significant improvements. The presentation is confined to Euclidean affine geometry, though the authors indicate whenever the treatment can be extended to curves and surfaces. The prerequisites for using the book are few, which will make it ideal for teaching advanced undergraduate or beginning graduate courses in computational geometry.

This 1997 book examines recent changes in the design of intelligent machines. New computer models of vision and navigation in animals suggest a different way to build machines. Cognition is viewed not just in terms of high-level 'expertise,' but in the ability to find one's way around the world, to learn new ways of seeing things, and to coordinate activity. This approach is called situated cognition. Situated Cognition differs from other purely philosophical treatises in that Clancey, an insider who has built expert systems for twenty years, explores the limitations of existing computer programs and compares them to human memory and learning capabilities. Clancey examines the implications of 'situated action' from the perspective of artificial intelligence specialists interested in building robots.

This 1997 book examines recent changes in the design of intelligent machines. New computer models of vision and navigation in animals suggest a different way to build machines. Cognition is viewed not just in terms of high-level 'expertise,' but in the ability to find one's way around the world, to learn new ways of seeing things, and to coordinate activity. This approach is called situated cognition. Situated Cognition differs from other purely philosophical treatises in that Clancey, an insider who has built expert systems for twenty years, explores the limitations of existing computer programs and compares them to human memory and learning capabilities. Clancey examines the implications of 'situated action' from the perspective of artificial intelligence specialists interested in building robots.

Bayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. This 1996 book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modelling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.

This volume of original papers has been assembled to honor Azriel Rosenfeld, the dominant figure in the field of computer vision and image processing for over 30 years. Over this period he has made ma

This monograph is devoted to the problem of inferring geometric information about arbitrarily curved surfaces from visual cues; this is a central problem in computer vision with immediate relevance fo

In his classsic book, Mindstorms: Children, Computers, and powerful Ideas, Seymour Papert set out a vision of how computers could change school. In The Children’s Machine he now looks back over a deca

Professor Colin Blakemore presents a fascinating insight to all the major topics in visual science research. Experts from around the world show how this vast subject can be unified from the viewpoint that describes the way in which visual systems efficiently encode and represent the outside world. The approach, which is both rigorous and general, was championed by H. B. Barlow in the fifties and has recently acquired a new significance in the light of exciting developments in computer science and artificial intelligence and vision. The book is essential reading for advanced undergraduates, postgraduates and researchers in the field of vision research and neuroscience.

In this book, the author presents a new vision of learning through design and production, and describes computer programming as a source of a learning and design power. As means of studying this exten

The study of spatial processes and their applications is an important topic in statistics and finds wide application particularly in computer vision and image processing. This book is devoted to statistical inference in spatial statistics and is intended for specialists needing an introduction to the subject and to its applications. One of the themes of the book is the demonstration of how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of lack of a unique asymptotic setting in spatial problems. Throughout, the author discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarising of images. Thus, the book will find wide appeal

What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena - including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For instance, should the mind be modeled by digital computers, or by parallel-processing systems more like brains? Do computer programs consist of meaningless patterns, or do they embody (and explain) genuine meaning?

近年來，深度學習的相關演算法已被廣泛使用在電腦視覺(computer vision)、神經機器翻譯(neural machine translation)、神經風格轉換(neural style transfer)及聊天機器人(chatbots)等的應用。 雖然網路上已經提供了許多深度學習的各種演算法程式，但若只會使用程式卻不瞭解各種演算法的內涵，對於深度學習的領域只能是見樹不見林，無法真正體會深

《電腦視覺檢測逆問題導論》(Introduction to Inverse Problems in Computer Vision Inspection) 一書介紹了利用電腦視覺這一嶄新的技術手段進行無接觸、高速的目標檢測和測量方法, 以及為達到其目標所採用的數學逆問題處理手段。本書從數學逆問題的角度歸納了電腦視覺處理圖像的常用技術, 解析了相關的數學方法, 較為系統介紹了利用電腦視覺進行檢測一些