Emerging Trends in Visual Computing

Emerging Trends in Visual Computing

Author: Frank Nielsen

Publisher: Springer Science & Business Media

Published: 2009-03-26

Total Pages: 397

ISBN-13: 3642008259

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of Symmetries and Repeated Patterns in 3D Point Cloud Data – Sylvain LAZARD (VEGAS, INRIA LORIA Nancy, France): 3D Visibility and Lines in Space VI Preface ´


Emerging Trends in Computing, Informatics, Systems Sciences, and Engineering

Emerging Trends in Computing, Informatics, Systems Sciences, and Engineering

Author: Tarek Sobh

Publisher: Springer Science & Business Media

Published: 2012-08-14

Total Pages: 1133

ISBN-13: 1461435587

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Emerging Trends in Computing, Informatics, Systems Sciences, and Engineering includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Industrial Electronics, Technology & Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning. This book includes the proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2010). The proceedings are a set of rigorously reviewed world-class manuscripts presenting the state of international practice in Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications.


Visual Computing for Medicine

Visual Computing for Medicine

Author: Bernhard Preim

Publisher: Newnes

Published: 2013-11-07

Total Pages: 1017

ISBN-13: 0124159796

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Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. The book includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered. Preim and Botha illustrate visualization techniques from research, but also cover the information required to solve practical clinical problems. They base the book on several years of combined teaching and research experience. This new edition includes six new chapters on treatment planning, guidance and training; an updated appendix on software support for visual computing for medicine; and a new global structure that better classifies and explains the major lines of work in the field. - Complete guide to visual computing in medicine, fully revamped and updated with new developments in the field - Illustrated in full color - Includes a companion website offering additional content for professors, source code, algorithms, tutorials, videos, exercises, lessons, and more


Computer Vision

Computer Vision

Author: Simon J. D. Prince

Publisher: Cambridge University Press

Published: 2012-06-18

Total Pages: 599

ISBN-13: 1139510568

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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


Information Theory in Computer Vision and Pattern Recognition

Information Theory in Computer Vision and Pattern Recognition

Author: Francisco Escolano Ruiz

Publisher: Springer Science & Business Media

Published: 2009-07-14

Total Pages: 375

ISBN-13: 1848822979

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Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.


Foundations of Computer Vision

Foundations of Computer Vision

Author: James F. Peters

Publisher: Springer

Published: 2017-03-17

Total Pages: 443

ISBN-13: 3319524836

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This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and first year graduate students in Engineering, Computer Science or Applied Mathematics. It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.


Deep Learning in Visual Computing and Signal Processing

Deep Learning in Visual Computing and Signal Processing

Author: Krishna Kant Singh

Publisher: CRC Press

Published: 2022-10-20

Total Pages: 289

ISBN-13: 1000565238

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Covers both the fundamentals and the latest concepts in deep learning Presents some of the diverse applications of deep learning in visual computing and signal processing Includes over 90 figures and tables to elucidate the text


New Trends in Computer Graphics

New Trends in Computer Graphics

Author: Nadia Magnenat-Thalmann

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 683

ISBN-13: 3642834922

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New Trends in Computer Graphics contains a selection of research papers submitted to Computer Graphics International '88 (COl '88). COl '88 is the Official Annual Conference of the Computer Graphics Society. Since 1982, this conference ha~ been held in Tokyo. This year, it is taking place in Geneva, Switzerland. In 1989, it will be held in Leeds, U. K. , in 1990 in Singapore, in 1991 in U. S. A. and in 1992 in Montreal, Canada. Over 100 papers were submitted to CGI '88 and 61 papers were selected by the International Program Committee. Papers have been grouped into 6 chapters. The flrst chapter is dedicated to Computer Animation because it deals with all topics presented in the other chapters. Several animation systems are described as well as speciflc subjects like 3D character animation, quaternions and splines. The second chapter is dedicated to papers on Image Synthesis, il1 particular new shading models and new algorithms for ray tracing are presented. Chapter 3 presents several algorithms for geometric modeling and new techniques for the creation and manipulation of curves, surfaces and solids and their applications to CAD. In Chapter 4, an important topic is presented: the specification of graphics systems and images using l~nguages and user-interfaces. The last two chapters are devoted to applications in sciences, medicine, engineering, art and business.


Computer Vision and Machine Intelligence for Renewable Energy Systems

Computer Vision and Machine Intelligence for Renewable Energy Systems

Author: Ashutosh Kumar Dubey

Publisher: Elsevier

Published: 2024-09-20

Total Pages: 389

ISBN-13: 0443289484

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Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source