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Applications Of Invariance In Computer Vision
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Book Synopsis Applications of Invariance in Computer Vision by : Joseph L. Mundy
Download or read book Applications of Invariance in Computer Vision written by Joseph L. Mundy and published by Springer Science & Business Media. This book was released on 1994-07-20 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the proceedings of the Second Joint European-US Workshop on Applications of Invariance to Computer Vision, held at Ponta Delgada, Azores, Portugal in October 1993. The book contains 25 carefully refereed papers by distinguished researchers. The papers cover all relevant foundational aspects of geometric and algebraic invariance as well as applications to computer vision, particularly to recovery and reconstruction, object recognition, scene analysis, robotic navigation, and statistical analysis. In total, the collection of papers, together with an introductory survey by the editors, impressively documents that geometry, in its different variants, is the most successful and ubiquitous tool in computer vision.
Book Synopsis Applications of Invariance in Computer Vision by : Joseph L. Mundy
Download or read book Applications of Invariance in Computer Vision written by Joseph L. Mundy and published by Springer. This book was released on 1994-07-20 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the proceedings of the Second Joint European-US Workshop on Applications of Invariance to Computer Vision, held at Ponta Delgada, Azores, Portugal in October 1993. The book contains 25 carefully refereed papers by distinguished researchers. The papers cover all relevant foundational aspects of geometric and algebraic invariance as well as applications to computer vision, particularly to recovery and reconstruction, object recognition, scene analysis, robotic navigation, and statistical analysis. In total, the collection of papers, together with an introductory survey by the editors, impressively documents that geometry, in its different variants, is the most successful and ubiquitous tool in computer vision.
Book Synopsis Applications of Invariance in Computer Vision by :
Download or read book Applications of Invariance in Computer Vision written by and published by . This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Geometric Invariance in Computer Vision by : Joseph L. Mundy
Download or read book Geometric Invariance in Computer Vision written by Joseph L. Mundy and published by . This book was released on 1992 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: These twenty-three contributions focus on the most recent developments in the rapidly evolving field of geometric invariants and their application to computer vision. The introduction summarizes the basics of invariant theory, discusses how invariants are related to problems in computer vision, and looks at the future possibilities, particularly the notion that invariant analysis might provide a solution to the elusive problem of recognizing general curved 3D objects from an arbitrary viewpoint. The remaining chapters consist of original papers that present important developments as well as tutorial articles that provide useful background material. These chapters are grouped into categories covering algebraic invariants, nonalgebraic invariants, invariants of multiple views, and applications. An appendix provides an extensive introduction to projective geometry and its applications to basic problems in computer vision.
Book Synopsis APPLICATIONS OF INVARIANCE IN COMPUTER VISION by : Joseph L. Mundy
Download or read book APPLICATIONS OF INVARIANCE IN COMPUTER VISION written by Joseph L. Mundy and published by . This book was released on 1994 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of Invariance in Computer Vision by : Joseph L. Mundy
Download or read book Applications of Invariance in Computer Vision written by Joseph L. Mundy and published by Springer. This book was released on 2014-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the proceedings of the Second Joint European-US Workshop on Applications of Invariance to Computer Vision, held at Ponta Delgada, Azores, Portugal in October 1993. The book contains 25 carefully refereed papers by distinguished researchers. The papers cover all relevant foundational aspects of geometric and algebraic invariance as well as applications to computer vision, particularly to recovery and reconstruction, object recognition, scene analysis, robotic navigation, and statistical analysis. In total, the collection of papers, together with an introductory survey by the editors, impressively documents that geometry, in its different variants, is the most successful and ubiquitous tool in computer vision.
Book Synopsis Applications of Invariance in Computer Vision by : Joseph L. Mundy
Download or read book Applications of Invariance in Computer Vision written by Joseph L. Mundy and published by . This book was released on 1991* with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Invariants For Pattern Recognition And Classification by : Marcos A Rodrigues
Download or read book Invariants For Pattern Recognition And Classification written by Marcos A Rodrigues and published by World Scientific. This book was released on 2000-12-29 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was conceived from the realization that there was a need to update recent work on invariants in a single volume providing a useful set of references and pointers to related work. Since the publication in 1992 of J L Mundy and A Zisserman's Geometric Invariance in Computer Vision, the subject has been evolving rapidly. New approaches to invariants have been proposed and novel ways of defining and applying invariants to practical problem solving are testimony to the fundamental importance of the study of invariants to machine vision. This book represents a snapshot of current research around the world.A version of this collection of papers has appeared in the International Journal of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published in the journal. They are organized into two categories: foundations and applications. Foundation papers present new ways of defining or analyzing invariants, and application papers present novel ways in which known invariant theory is extended and effectively applied to real-world problems in interesting and difficult contexts. Each category contains roughly half of the papers, but there is considerable overlap. All papers carry an element of novelty and generalization that will be useful to theoreticians and practitioners alike. It is hoped that this volume will be not only useful but also inspirational to researchers in image processing, pattern recognition and computer vision at large.
Book Synopsis Color in Computer Vision by : Theo Gevers
Download or read book Color in Computer Vision written by Theo Gevers and published by John Wiley & Sons. This book was released on 2012-08-14 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the field of computer vision drives many of today’s digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding. Based on the authors’ intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color in Computer Vision explains: Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations Signal processing techniques for the development of both image processing and machine learning Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field.
Book Synopsis Computer Vision - ECCV 2008 by : David Hutchison
Download or read book Computer Vision - ECCV 2008 written by David Hutchison and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Book Synopsis Computer Vision Metrics by : Scott Krig
Download or read book Computer Vision Metrics written by Scott Krig and published by Apress. This book was released on 2014-06-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.
Book Synopsis Local Invariant Feature Detectors by : Tinne Tuytelaars
Download or read book Local Invariant Feature Detectors written by Tinne Tuytelaars and published by Now Publishers Inc. This book was released on 2008 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Local Invariant Features Detectors is an overview of invariant interest point detectors, how they evolved over time, how they work, and what their respective strengths and weaknesses are.
Book Synopsis Covariances in Computer Vision and Machine Learning by : Hà Quang Minh
Download or read book Covariances in Computer Vision and Machine Learning written by Hà Quang Minh and published by Morgan & Claypool Publishers. This book was released on 2017-11-07 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covariance matrices play important roles in many areas of mathematics, statistics, and machine learning, as well as their applications. In computer vision and image processing, they give rise to a powerful data representation, namely the covariance descriptor, with numerous practical applications. In this book, we begin by presenting an overview of the {\it finite-dimensional covariance matrix} representation approach of images, along with its statistical interpretation. In particular, we discuss the various distances and divergences that arise from the intrinsic geometrical structures of the set of Symmetric Positive Definite (SPD) matrices, namely Riemannian manifold and convex cone structures. Computationally, we focus on kernel methods on covariance matrices, especially using the Log-Euclidean distance. We then show some of the latest developments in the generalization of the finite-dimensional covariance matrix representation to the {\it infinite-dimensional covariance operator} representation via positive definite kernels. We present the generalization of the affine-invariant Riemannian metric and the Log-Hilbert-Schmidt metric, which generalizes the Log Euclidean distance. Computationally, we focus on kernel methods on covariance operators, especially using the Log-Hilbert-Schmidt distance. Specifically, we present a two-layer kernel machine, using the Log-Hilbert-Schmidt distance and its finite-dimensional approximation, which reduces the computational complexity of the exact formulation while largely preserving its capability. Theoretical analysis shows that, mathematically, the approximate Log-Hilbert-Schmidt distance should be preferred over the approximate Log-Hilbert-Schmidt inner product and, computationally, it should be preferred over the approximate affine-invariant Riemannian distance. Numerical experiments on image classification demonstrate significant improvements of the infinite-dimensional formulation over the finite-dimensional counterpart. Given the numerous applications of covariance matrices in many areas of mathematics, statistics, and machine learning, just to name a few, we expect that the infinite-dimensional covariance operator formulation presented here will have many more applications beyond those in computer vision.
Book Synopsis Emerging Topics in Computer Vision and Its Applications by : C. H. Chen
Download or read book Emerging Topics in Computer Vision and Its Applications written by C. H. Chen and published by World Scientific. This book was released on 2012 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.
Book Synopsis Color in Computer Vision by : Theo Gevers
Download or read book Color in Computer Vision written by Theo Gevers and published by John Wiley & Sons. This book was released on 2012-09-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the field of computer vision drives many of today’s digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding. Based on the authors’ intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color in Computer Vision explains: Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations Signal processing techniques for the development of both image processing and machine learning Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field.
Book Synopsis Theoretical Foundations of Computer Vision by : Walter Kropatsch
Download or read book Theoretical Foundations of Computer Vision written by Walter Kropatsch and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision is a rapidly growing field of research investigating computational and algorithmic issues associated with image acquisition, processing, and understanding. It serves tasks like manipulation, recognition, mobility, and communication in diverse application areas such as manufacturing, robotics, medicine, security and virtual reality. This volume contains a selection of papers devoted to theoretical foundations of computer vision covering a broad range of fields, e.g. motion analysis, discrete geometry, computational aspects of vision processes, models, morphology, invariance, image compression, 3D reconstruction of shape. Several issues have been identified to be of essential interest to the community: non-linear operators; the transition between continuous to discrete representations; a new calculus of non-orthogonal partially dependent systems.
Book Synopsis Applications of Geometric Invariants to Computer Vision - AASERT Grant by :
Download or read book Applications of Geometric Invariants to Computer Vision - AASERT Grant written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an AASERT grant that is a supplementary award to the parent AFOSR Grant FR962O-94-1-OO2. The objective was to train a graduate student who must be a U.S. citizen. We have achieved this objective and the student will be awarded a Ph. D. in Computer Science in August 1997. Also, the student published several papers in refereed journals and gave oral presentations in two international conferences. We developed a method for object recognition by extracting conics from digitized images and computing their invariants. The proposed method was extensively tested under noisy conditions and the results were highly satisfactory. We also investigated the geometrical properties of the Legendre transform that are of interest in image understanding applications. Finally, we developed a matching algorithm for space curves, which reduces the problem to finding the eigenvalues of a 4-dimensional matrix.
