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Handbook Of Mathematical Models In Computer Vision
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Book Synopsis Handbook of Mathematical Models in Computer Vision by : Nikos Paragios
Download or read book Handbook of Mathematical Models in Computer Vision written by Nikos Paragios and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr's theory v^as a pioneering step tov^ards understanding visual percep tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest.
Book Synopsis Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging by : Ke Chen
Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by Springer Nature. This book was released on 2023-02-24 with total page 1981 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
Book Synopsis Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging by : Ke Chen
Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Computer Vision and Applications: Systems and applications by : Bernd Jähne
Download or read book Handbook of Computer Vision and Applications: Systems and applications written by Bernd Jähne and published by . This book was released on 1999 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM files contain complete text of all three print vols., as well as hyperlinks to figures, tables, etc. and between the index and the text. Also included are hyperlinks to movies, interactive 3-D models, demonstration software and other materials not contained in the print version.
Book Synopsis Handbook of Mathematical Methods in Imaging by : Otmar Scherzer
Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.
Book Synopsis Handbook Of Pattern Recognition And Computer Vision (2nd Edition) by : Chi Hau Chen
Download or read book Handbook Of Pattern Recognition And Computer Vision (2nd Edition) written by Chi Hau Chen and published by World Scientific. This book was released on 1999-03-12 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
Book Synopsis Handbook of Computer Vision Algorithms in Image Algebra by : Joseph N. Wilson
Download or read book Handbook of Computer Vision Algorithms in Image Algebra written by Joseph N. Wilson and published by CRC Press. This book was released on 2000-09-21 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image algebra is a comprehensive, unifying theory of image transformations, image analysis, and image understanding. In 1996, the bestselling first edition of the Handbook of Computer Vision Algorithms in Image Algebra introduced engineers, scientists, and students to this powerful tool, its basic concepts, and its use in the concise representation
Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Book Synopsis Computer Vision by : Simon J. D. Prince
Download or read book Computer Vision written by Simon J. D. Prince and published by Cambridge University Press. This book was released on 2012-06-18 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Author :Françoise Prêteux Publisher :SPIE-International Society for Optical Engineering ISBN 13 : Total Pages :322 pages Book Rating :4.3/5 (91 download)
Book Synopsis Mathematical Modeling and Estimation Techniques in Computer Vision by : Françoise Prêteux
Download or read book Mathematical Modeling and Estimation Techniques in Computer Vision written by Françoise Prêteux and published by SPIE-International Society for Optical Engineering. This book was released on 1998 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Introduction to Mathematical Modeling by : Edward A. Bender
Download or read book An Introduction to Mathematical Modeling written by Edward A. Bender and published by Courier Corporation. This book was released on 2012-05-23 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.
Book Synopsis Photogrammetric Computer Vision by : Wolfgang Förstner
Download or read book Photogrammetric Computer Vision written by Wolfgang Förstner and published by Springer. This book was released on 2016-10-04 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers a statistical view on the geometry of multiple view analysis, required for camera calibration and orientation and for geometric scene reconstruction based on geometric image features. The authors have backgrounds in geodesy and also long experience with development and research in computer vision, and this is the first book to present a joint approach from the converging fields of photogrammetry and computer vision. Part I of the book provides an introduction to estimation theory, covering aspects such as Bayesian estimation, variance components, and sequential estimation, with a focus on the statistically sound diagnostics of estimation results essential in vision metrology. Part II provides tools for 2D and 3D geometric reasoning using projective geometry. This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their relations, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is devoted to modelling the geometry of single and multiple cameras, addressing calibration and orientation, including statistical evaluation and reconstruction of corresponding scene features and surfaces based on geometric image features. The authors provide algorithms for various geometric computation problems in vision metrology, together with mathematical justifications and statistical analysis, thus enabling thorough evaluations. The chapters are self-contained with numerous figures and exercises, and they are supported by an appendix that explains the basic mathematical notation and a detailed index. The book can serve as the basis for undergraduate and graduate courses in photogrammetry, computer vision, and computer graphics. It is also appropriate for researchers, engineers, and software developers in the photogrammetry and GIS industries, particularly those engaged with statistically based geometric computer vision methods.
Book Synopsis Computer Vision by : Simon J. D. Prince
Download or read book Computer Vision written by Simon J. D. Prince and published by Cambridge University Press. This book was released on 2012-06-18 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision. • Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry • A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition and object tracking • More than 70 algorithms are described in sufficient detail to implement • More than 350 full-color illustrations amplify the text • The treatment is self-contained, including all of the background mathematics • Additional resources at www.computervisionmodels.com
Book Synopsis Handbook of Graphical Models by : Marloes Maathuis
Download or read book Handbook of Graphical Models written by Marloes Maathuis and published by CRC Press. This book was released on 2018-11-12 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art. Key features: * Contributions by leading researchers from a range of disciplines * Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications * Balanced coverage of concepts, theory, methods, examples, and applications * Chapters can be read mostly independently, while cross-references highlight connections The handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.
Download or read book Image Fusion written by Tania Stathaki and published by Elsevier. This book was released on 2011-08-29 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image Fusion: Algorithms and Applications provides a representative collection of the recent advances in research and development in the field of image fusion, demonstrating both spatial domain and transform domain fusion methods including Bayesian methods, statistical approaches, ICA and wavelet domain techniques. It also includes valuable material on image mosaics, remote sensing applications and performance evaluation. This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications. Combines theory and practice to create a unique point of reference Contains contributions from leading experts in this rapidly-developing field Demonstrates potential uses in military, medical and civilian areas
Book Synopsis Simulation and Analysis of Mathematical Methods in Real-Time Engineering Applications by : T. Ananth Kumar
Download or read book Simulation and Analysis of Mathematical Methods in Real-Time Engineering Applications written by T. Ananth Kumar and published by John Wiley & Sons. This book was released on 2021-08-16 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: SIMULATIONS AND ANALYSIS of Mathematical Methods Written and edited by a group of international experts in the field, this exciting new volume covers the state of the art of real-time applications of computer science using mathematics. This breakthrough edited volume highlights the security, privacy, artificial intelligence, and practical approaches needed by engineers and scientists in all fields of science and technology. It highlights the current research, which is intended to advance not only mathematics but all areas of science, research, and development, and where these disciplines intersect. As the book is focused on emerging concepts in machine learning and artificial intelligence algorithmic approaches and soft computing techniques, it is an invaluable tool for researchers, academicians, data scientists, and technology developers. The newest and most comprehensive volume in the area of mathematical methods for use in real-time engineering, this groundbreaking new work is a must-have for any engineer or scientist’s library. Also useful as a textbook for the student, it is a valuable contribution to the advancement of the science, both a working handbook for the new hire or student, and a reference for the veteran engineer.
Book Synopsis Shape Reconstruction from Apparent Contours by : Giovanni Bellettini
Download or read book Shape Reconstruction from Apparent Contours written by Giovanni Bellettini and published by Springer. This book was released on 2015-02-25 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by a variational model concerning the depth of the objects in a picture and the problem of hidden and illusory contours, this book investigates one of the central problems of computer vision: the topological and algorithmic reconstruction of a smooth three dimensional scene starting from the visible part of an apparent contour. The authors focus their attention on the manipulation of apparent contours using a finite set of elementary moves, which correspond to diffeomorphic deformations of three dimensional scenes. A large part of the book is devoted to the algorithmic part, with implementations, experiments, and computed examples. The book is intended also as a user's guide to the software code appcontour, written for the manipulation of apparent contours and their invariants. This book is addressed to theoretical and applied scientists working in the field of mathematical models of image segmentation.
