Information Theory Tools For Computer Graphics
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Information Theory Tools For Computer Graphics
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Author : Mateu Sbert
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2009-12-08
Information Theory Tools For Computer Graphics written by Mateu Sbert and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-08 with Technology & Engineering categories.
Information theory (IT) tools, widely used in scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also emerging as useful transversal tools in computer graphics. In this book, we present the basic concepts of IT and how they have been applied to the graphics areas of radiosity, adaptive ray-tracing, shape descriptors, viewpoint selection and saliency, scientific visualization, and geometry simplification. Some of the approaches presented, such as the viewpoint techniques, are now the state of the art in visualization. Almost all of the techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. Here, we have stressed their common aspects and presented them in an unified way, so the reader can clearly see which problems IT tools can help solve, which specific tools to use, and how to apply them. A basic level of knowledge in computer graphics is required but basic concepts in IT are presented. The intended audiences are both students and practitioners of the fields above and related areas in computer graphics. In addition, IT practitioners will learn about these applications. Table of Contents: Information Theory Basics / Scene Complexity and Refinement Criteria for Radiosity / Shape Descriptors / Refinement Criteria for Ray-Tracing / Viewpoint Selection and Mesh Saliency / View Selection in Scientific Visualization / Viewpoint-based Geometry Simplification
Information Theory Tools For Visualization
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Author : Min Chen
language : en
Publisher: CRC Press
Release Date : 2016-09-19
Information Theory Tools For Visualization written by Min Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-19 with Computers categories.
This book explores Information theory (IT) tools, which have become state of the art to solve and understand better many of the problems in visualization. This book covers all relevant literature up to date. It is the first book solely devoted to this subject, written by leading experts in the field.
Information Theory Tools For Image Processing
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Author : Miquel Feixas
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Information Theory Tools For Image Processing written by Miquel Feixas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Mathematics categories.
Information Theory (IT) tools, widely used in many scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also useful transversal tools in image processing. In this book, we present the basic concepts of IT and how they have been used in the image processing areas of registration, segmentation, video processing, and computational aesthetics. Some of the approaches presented, such as the application of mutual information to registration, are the state of the art in the field. All techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. We have stressed here their common aspects, and presented them in an unified way, so to make clear to the reader which problems IT tools can help to solve, which specific tools to use, and how to apply them. The IT basics are presented so as to be self-contained in the book. The intended audiences are students and practitioners of image processing and related areas such as computer graphics and visualization. In addition, students and practitioners of IT will be interested in knowing about these applications. Table of Contents: Preface / Acknowledgments / Information Theory Basics / Image Registration / Image Segmentation / Video Key Frame Selection / Informational Aesthetics Measures / Bibliography / Authors' Biographies
Information Theory Tools For Computer Graphics
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Author : Mateu Sbert
language : en
Publisher: Springer
Release Date : 2009-09-09
Information Theory Tools For Computer Graphics written by Mateu Sbert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-09 with Mathematics categories.
Information theory (IT) tools, widely used in scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also emerging as useful transversal tools in computer graphics. In this book, we present the basic concepts of IT and how they have been applied to the graphics areas of radiosity, adaptive ray-tracing, shape descriptors, viewpoint selection and saliency, scientific visualization, and geometry simplification. Some of the approaches presented, such as the viewpoint techniques, are now the state of the art in visualization. Almost all of the techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. Here, we have stressed their common aspects and presented them in an unified way, so the reader can clearly see which problems IT tools can help solve, which specific tools to use, and how to apply them. A basic level of knowledge in computer graphics is required but basic concepts in IT are presented. The intended audiences are both students and practitioners of the fields above and related areas in computer graphics. In addition, IT practitioners will learn about these applications. Table of Contents: Information Theory Basics / Scene Complexity and Refinement Criteria for Radiosity / Shape Descriptors / Refinement Criteria for Ray-Tracing / Viewpoint Selection and Mesh Saliency / View Selection in Scientific Visualization / Viewpoint-based Geometry Simplification
Geometric Tools For Computer Graphics
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Author : Philip Schneider
language : en
Publisher: Elsevier
Release Date : 2002-10-10
Geometric Tools For Computer Graphics written by Philip Schneider and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-10-10 with Computers categories.
Do you spend too much time creating the building blocks of your graphics applications or finding and correcting errors? Geometric Tools for Computer Graphics is an extensive, conveniently organized collection of proven solutions to fundamental problems that you'd rather not solve over and over again, including building primitives, distance calculation, approximation, containment, decomposition, intersection determination, separation, and more. If you have a mathematics degree, this book will save you time and trouble. If you don't, it will help you achieve things you may feel are out of your reach. Inside, each problem is clearly stated and diagrammed, and the fully detailed solutions are presented in easy-to-understand pseudocode. You also get the mathematics and geometry background needed to make optimal use of the solutions, as well as an abundance of reference material contained in a series of appendices. Features - Filled with robust, thoroughly tested solutions that will save you time and help you avoid costly errors. - Covers problems relevant for both 2D and 3D graphics programming. - Presents each problem and solution in stand-alone form allowing you the option of reading only those entries that matter to you. - Provides the math and geometry background you need to understand the solutions and put them to work. - Clearly diagrams each problem and presents solutions in easy-to-understand pseudocode. - Resources associated with the book are available at the companion Web site www.mkp.com/gtcg.* Filled with robust, thoroughly tested solutions that will save you time and help you avoid costly errors.* Covers problems relevant for both 2D and 3D graphics programming.* Presents each problem and solution in stand-alone form allowing you the option of reading only those entries that matter to you.* Provides the math and geometry background you need to understand the solutions and put them to work.* Clearly diagrams each problem and presents solutions in easy-to-understand pseudocode.* Resources associated with the book are available at the companion Web site www.mkp.com/gtcg.
An Introduction To Verification Of Visualization Techniques
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Author : Tiago Etiene
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
An Introduction To Verification Of Visualization Techniques written by Tiago Etiene and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Mathematics categories.
As we increase our reliance on computer-generated information, often using it as part of our decision-making process, we must devise tools to assess the correctness of that information. Consider, for example, software embedded on vehicles, used for simulating aircraft performance, or used in medical imaging. In those cases, software correctness is of paramount importance as there's little room for error. Software verification is one of the tools available to attain such goals. Verification is a well known and widely studied subfield of computer science and computational science and the goal is to help us increase confidence in the software implementation by verifying that the software does what it is supposed to do. The goal of this book is to introduce the reader to software verification in the context of visualization. In the same way we became more dependent on commercial software, we have also increased our reliance on visualization software. The reason is simple: visualization is the lens through which users can understand complex data, and as such it must be verified. The explosion in our ability to amass data requires tools not only to store and analyze data, but also to visualize it. This book is comprised of six chapters. After an introduction to the goals of the book, we present a brief description of both worlds of visualization (Chapter 2) and verification (Chapter 3). We then proceed to illustrate the main steps of the verification pipeline for visualization algorithms. We focus on two classic volume visualization techniques, namely, Isosurface Extraction (Chapter 4) and Direct Volume Rendering (Chapter 5). We explain how to verify implementations of those techniques and report the latest results in the field of verification of visualization techniques. The last chapter concludes the book and highlights new research topics for the future.
Information Theory Tools For Visualization
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Author : Min Chen
language : en
Publisher: CRC Press
Release Date : 2016-09-19
Information Theory Tools For Visualization written by Min Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-19 with Computers categories.
This book explores Information theory (IT) tools, which have become state of the art to solve and understand better many of the problems in visualization. This book covers all relevant literature up to date. It is the first book solely devoted to this subject, written by leading experts in the field.
An Introduction To Laplacian Spectral Distances And Kernels
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Author : Giuseppe Patanè
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
An Introduction To Laplacian Spectral Distances And Kernels written by Giuseppe Patanè and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Mathematics categories.
In geometry processing and shape analysis, several applications have been addressed through the properties of the Laplacian spectral kernels and distances, such as commute time, biharmonic, diffusion, and wave distances. Within this context, this book is intended to provide a common background on the definition and computation of the Laplacian spectral kernels and distances for geometry processing and shape analysis. To this end, we define a unified representation of the isotropic and anisotropic discrete Laplacian operator on surfaces and volumes; then, we introduce the associated differential equations, i.e., the harmonic equation, the Laplacian eigenproblem, and the heat equation. Filtering the Laplacian spectrum, we introduce the Laplacian spectral distances, which generalize the commute-time, biharmonic, diffusion, and wave distances, and their discretization in terms of the Laplacian spectrum. As main applications, we discuss the design of smooth functions and the Laplacian smoothing of noisy scalar functions. All the reviewed numerical schemes are discussed and compared in terms of robustness, approximation accuracy, and computational cost, thus supporting the reader in the selection of the most appropriate with respect to shape representation, computational resources, and target application.
Stochastic Partial Differential Equations For Computer Vision With Uncertain Data
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Author : Tobias Preusser
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Stochastic Partial Differential Equations For Computer Vision With Uncertain Data written by Tobias Preusser and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Mathematics categories.
In image processing and computer vision applications such as medical or scientific image data analysis, as well as in industrial scenarios, images are used as input measurement data. It is good scientific practice that proper measurements must be equipped with error and uncertainty estimates. For many applications, not only the measured values but also their errors and uncertainties, should be—and more and more frequently are—taken into account for further processing. This error and uncertainty propagation must be done for every processing step such that the final result comes with a reliable precision estimate. The goal of this book is to introduce the reader to the recent advances from the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). It presents a concept with which error propagation and sensitivity analysis can be formulated with a set of basic operations. The approach discussed in this book has the potential for application in all areas of quantitative computer vision, image processing, and image analysis. In particular, it might help medical imaging finally become a scientific discipline that is characterized by the classical paradigms of observation, measurement, and error awareness. This book is comprised of eight chapters. After an introduction to the goals of the book (Chapter 1), we present a brief review of PDEs and their numerical treatment (Chapter 2), PDE-based image processing (Chapter 3), and the numerics of stochastic PDEs (Chapter 4). We then proceed to define the concept of stochastic images (Chapter 5), describe how to accomplish image processing and computer vision with stochastic images (Chapter 6), and demonstrate the use of these principles for accomplishing sensitivity analysis (Chapter 7). Chapter 8 concludes the book and highlights new research topics for the future.
Advances In Info Metrics
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Author : Min Chen
language : en
Publisher: Oxford University Press
Release Date : 2020-11-14
Advances In Info Metrics written by Min Chen and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-14 with Business & Economics categories.
Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.