Computer Vision

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

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.

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.

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

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.

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

This collection of 38 papers and 29 posters from the May 2004 conference reports on research and development activities in computer vision, robot vision, image processing, medical imaging, and pattern

This book brings together novel concepts in machine vision, computer graphics, and threedimensional modelling, in solving real practical inspection problems. Automated inspection of three-dimensional

Smartphones, nuclear warheads, moon bases, computers . . . all bear the fingerprints of one remarkable man: John von Neumann. Born in Budapest in 1903, he moved to America in 1930 and--in his work as mathematician, physicist, computer scientist, and engineer--became one of the most influential scientists of the century. Von Neumann was instrumental in the Manhattan Project and the design of the atom bomb; he helped formulate game theory, the bedrock of Cold War geopolitics and modern economic theory; he created the programmable digital computer; he prophesized the potential of nanotechnology; and, from his deathbed, he outlined a vision of artificial intelligence.In telling the story of Von Neumann's life and ideas, Ananyo Bhattacharya explores how a combination of genius and historical circumstance allowed one man to sweep through so many different fields of science, sparking revolutions wherever he went. The Man from the Future is a thrilling biography of a visionary thinker who shap

【本書特色】 最貼近新手的深度學習理論及應用全方位入門書！ ✪學習必備理論，打好基礎，新手不怕被過多的數學式嚇跑。 ✪使用PyTorch直覺易懂且強大的深度學習框架，開始應用的第一步。 ✪了解自然語言處理、電腦視覺與強化學習等三大領域經典應用與實作，領略深度學習的強大。 ✪兼顧理論與實作，而非偏頗一方，培養讀者較全面的理解。 ✪包含經典學術論文與知名專案技術講解，幫助讀者掌握此技術所能到達的高度。 ✪每章末提供自我檢驗題目，幫助理解與統整各章概念。 【內容簡介】 本書內容改編自第12屆iT邦幫忙鐵人賽AI & Data組冠軍系列文章《Knock Knock！Deep Learning》，是專為深度學習初學者所規劃的內容，旨在以淺顯易懂的文字，帶領深度學習領域的新手度過入門撞牆期。內容從深度學習的基本理論開始，並以PyTorch框架的介紹過渡至應用篇，最後以自然語言處理、電腦視覺與強化學習等三大領域的經典論文與實作專案收尾，循序漸進且去蕪存菁。本書會帶入許多故事性的敘述和插圖，結合作者自身在史丹佛大學修讀碩士期間的學習心得，以及深度學習發展相關的故事，期使本書讀起來不會如教科書一樣厚重，亦不會像網路上的技術文章一般零散無脈絡，讓讀者對深度學習領域的發展有一定的概念。 【內容重點】 ✪了解深度學習的基礎理論以及必備的實作知識與工具 內容從人類的神經網路開始，介紹深度學習與其相似之處，並理解神經網路的學習步驟，同時也介紹一些必備的實作知識與工具，以具備基本的實作工程技能。 ✪入門深度學習框架PyTorch 內容介紹語法簡潔、好上手且在學術界流行的PyTorch框架，著重實作與應用。 ✪深度學習×自然語言處理×電腦視覺×強化學習 內容會依序談到深度學習在三方面的應用，如自然語言處理（Natural Language Processing，NLP )、電腦視覺（Computer Vision，CV )、強化學習（Reinforcement Learning，RL )。除了基本簡介外，還會介紹一些基本實作和改變世界的技術成果。 【適用讀者】 ✪對深度學習有興趣，但還不知道它是什麼、能做什麼的新手。 ✪零散讀過深度學習相關文章，但仍有知識缺口的入門者。 ✪被教科書中龐大的數學理論嚇到，而對深度學習卻步的讀者。 ✪正在上學校的深度學習課程，但不知道實作從何開始的學生。

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

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

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

Computer scientists describe the current understanding and practice of machine learning, both supervised and unsupervised, in a range of fields. They cover mobile vision for a plant biometric syste

《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

Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3About This BookGet to grips with the basics of Computer Vision and image processingThis

Expand your knowledge of computer vision by building amazing projects with OpenCV 3About This BookBuild computer vision projects to capture high-quality image data, detect and track objects, process t

Build real-world computer vision applications and develop cool demos using OpenCV for PythonAbout This BookLearn how to apply complex visual effects to images using geometric transformations and image

If you are a Java developer who is new to computer vision and would like to learn through application development, then this book is for you. You are expected to have a mobile device running Android 2

This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: pr

An ongoing effort is being made in the field of computer vision to refine algorithms for optimal/better performance, which can mean reliability and increased computational speed. This is highly impor

《MATLAB圖像處理：程序實現與模塊化仿真》深入淺出地介紹了MATLAB 2012計算機視覺工具箱（Computer Vision System）、數字圖像處理工具箱的最新功能，并以此為編程工具闡述了數字圖像／視頻的基礎理論、關鍵技術、應用實例、解決方案、發展前沿。《MATLAB圖像處理：程序實現與模塊化仿真》共8章，內容包括：MATLAB數字圖像／視頻處理

The authors of "OpenCV" explain how to put computer vision to work. They bring readers up to speed with the latest updates in the field and show them how to program with existing free code.

In the areas of image processing and computer vision, there is a particular need for software that can, given an unfocused or motion-blurred image, infer the three-dimensional shape of a scene. This b