Three-Dimensional Object Recognition Systems

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ISBN 13 :
Total Pages : 488 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Three-Dimensional Object Recognition Systems by : Anil K Jain

Download or read book Three-Dimensional Object Recognition Systems written by Anil K Jain and published by . This book was released on 1993-05-05 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design and construction of three-dimensional [3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains. The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.

Three-Dimensional Object Recognition from Range Images

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Publisher : Springer Science & Business Media
ISBN 13 : 4431682139
Total Pages : 318 pages
Book Rating : 4.4/5 (316 download)

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Book Synopsis Three-Dimensional Object Recognition from Range Images by : Minsoo Suk

Download or read book Three-Dimensional Object Recognition from Range Images written by Minsoo Suk and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. T08iyasu L. Kunii PREFACE The primary aim of this book is to present a coherent and self-contained de scription of recent advances in three-dimensional object recognition from range images. Three-dimensional object recognition concerns recognition and localiza tion of objects of interest in a scene from input images. This problem is one of both theoretical and practical importance. On the theoretical side, it is an ideal vehicle for the study of the general area of computer vision since it deals with several important issues encountered in computer vision-for example, issues such as feature extraction, acquisition, representation and proper use of knowl edge, employment of efficient control strategies, coupling numerical and symbolic computations, and parallel implementation of algorithms. On the practical side, it has a wide range of applications in areas such as robot vision, autonomous navigation, automated inspection of industrial parts, and automated assembly.

Three-dimensional Computer Vision

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Publisher : MIT Press
ISBN 13 : 9780262061582
Total Pages : 712 pages
Book Rating : 4.0/5 (615 download)

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Book Synopsis Three-dimensional Computer Vision by : Olivier Faugeras

Download or read book Three-dimensional Computer Vision written by Olivier Faugeras and published by MIT Press. This book was released on 1993 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph by one of the world's leading vision researchers provides a thorough, mathematically rigorous exposition of a broad and vital area in computer vision: the problems and techniques related to three-dimensional (stereo) vision and motion. The emphasis is on using geometry to solve problems in stereo and motion, with examples from navigation and object recognition. Faugeras takes up such important problems in computer vision as projective geometry, camera calibration, edge detection, stereo vision (with many examples on real images), different kinds of representations and transformations (especially 3-D rotations), uncertainty and methods of addressing it, and object representation and recognition. His theoretical account is illustrated with the results of actual working programs.Three-Dimensional Computer Vision proposes solutions to problems arising from a specific robotics scenario in which a system must perceive and act. Moving about an unknown environment, the system has to avoid static and mobile obstacles, build models of objects and places in order to be able to recognize and locate them, and characterize its own motion and that of moving objects, by providing descriptions of the corresponding three-dimensional motions. The ideas generated, however, can be used indifferent settings, resulting in a general book on computer vision that reveals the fascinating relationship of three-dimensional geometry and the imaging process.

An Introduction to Object Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 1849962359
Total Pages : 210 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis An Introduction to Object Recognition by : Marco Alexander Treiber

Download or read book An Introduction to Object Recognition written by Marco Alexander Treiber and published by Springer Science & Business Media. This book was released on 2010-07-23 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly.

Three-dimensional Object Recognition from Single Two-dimensional Images

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (28 download)

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Book Synopsis Three-dimensional Object Recognition from Single Two-dimensional Images by : David G. Lowe

Download or read book Three-dimensional Object Recognition from Single Two-dimensional Images written by David G. Lowe and published by . This book was released on 1986 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "A computer vision system has been implemented that can recognize three-dimensional objects from unknown view points in single gray-scale images. Unlike most other approaches, the recognition is accomplished without any attempt to reconstruct depth information bottom-up from the visual input. Instead, three other mechanisms are used that can bridge the gap between the two-dimensional image and knowledge of three-dimensional objects. First, a process of perceptual organization is used to form groupings and structures in the image that are likely to be invariant over a wide range of viewpoints. Second, a probabilistic ranking method is used to reduce the size of the search space during model based matching. Finally, a process of spatial correspondence brings the projections of three-dimensional models into direct correspondence with the image by solving for unknown viewpoint and model parameters. A high level of robustness in the presence of occlusion and missing data can be achieved through full application of a viewpoint consistency constraint. It is argued that similar mechanisms and constraints form the basis for recognition in human vision."

Machine Vision for Three-Dimensional Scenes

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Publisher : Elsevier
ISBN 13 : 0323150632
Total Pages : 432 pages
Book Rating : 4.3/5 (231 download)

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Book Synopsis Machine Vision for Three-Dimensional Scenes by : Herbert Freeman

Download or read book Machine Vision for Three-Dimensional Scenes written by Herbert Freeman and published by Elsevier. This book was released on 2012-12-02 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Vision for Three-Dimensional Scenes contains the proceedings of the workshop "Machine Vision - Acquiring and Interpreting the 3D Scene" sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held in April 1989 in New Brunswick, New Jersey. The papers explore the applications of machine vision in image acquisition and 3D scene interpretation and cover topics such as segmentation of multi-sensor images; the placement of sensors to minimize occlusion; and the use of light striping to obtain range data. Comprised of 14 chapters, this book opens with a discussion on 3D object recognition and the problems that arise when dealing with large object databases, along with solutions to these problems. The reader is then introduced to the free-form surface matching problem and object recognition by constrained search. The following chapters address the problem of machine vision inspection, paying particular attention to the use of eye tracking to train a vision system; images of 3D scenes and the attendant problems of image understanding; the problem of object motion; and real-time range mapping. The final chapter assesses the relationship between the developing machine vision technology and the marketplace. This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608457281
Total Pages : 172 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Representations and Techniques for 3D Object Recognition and Scene Interpretation by : Derek Hoiem

Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Hoiem and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions

Representations and Techniques for 3D Object Recognition and Scene Interpretation

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Publisher : Springer Nature
ISBN 13 : 3031015576
Total Pages : 147 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Representations and Techniques for 3D Object Recognition and Scene Interpretation by : Derek Santhanam

Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Santhanam and published by Springer Nature. This book was released on 2022-05-31 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions

An Introduction to 3D Computer Vision Techniques and Algorithms

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Publisher : John Wiley & Sons
ISBN 13 : 1119964474
Total Pages : 485 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis An Introduction to 3D Computer Vision Techniques and Algorithms by : Boguslaw Cyganek

Download or read book An Introduction to 3D Computer Vision Techniques and Algorithms written by Boguslaw Cyganek and published by John Wiley & Sons. This book was released on 2011-08-10 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is possible to take a collection of stereo-pair images of a scene and then automatically produce a photo-realistic, geometrically accurate digital 3D model. This book provides a comprehensive introduction to the methods, theories and algorithms of 3D computer vision. Almost every theoretical issue is underpinned with practical implementation or a working algorithm using pseudo-code and complete code written in C++ and MatLab®. There is the additional clarification of an accompanying website with downloadable software, case studies and exercises. Organised in three parts, Cyganek and Siebert give a brief history of vision research, and subsequently: present basic low-level image processing operations for image matching, including a separate chapter on image matching algorithms; explain scale-space vision, as well as space reconstruction and multiview integration; demonstrate a variety of practical applications for 3D surface imaging and analysis; provide concise appendices on topics such as the basics of projective geometry and tensor calculus for image processing, distortion and noise in images plus image warping procedures. An Introduction to 3D Computer Vision Algorithms and Techniques is a valuable reference for practitioners and programmers working in 3D computer vision, image processing and analysis as well as computer visualisation. It would also be of interest to advanced students and researchers in the fields of engineering, computer science, clinical photography, robotics, graphics and mathematics.

Object Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 9781852333980
Total Pages : 376 pages
Book Rating : 4.3/5 (339 download)

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Book Synopsis Object Recognition by : M. Bennamoun

Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2001-12-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.

Analysis and Interpretation of Range Images

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Publisher : Springer Science & Business Media
ISBN 13 : 1461233607
Total Pages : 393 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Analysis and Interpretation of Range Images by : Ramesh C. Jain

Download or read book Analysis and Interpretation of Range Images written by Ramesh C. Jain and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision researchers have been frustrated in their attempts to automatically derive depth information from conventional two-dimensional intensity images. Research on "shape from texture", "shape from shading", and "shape from focus" is still in a laboratory stage and had not seen much use in commercial machine vision systems. A range image or a depth map contains explicit information about the distance from the sensor to the object surfaces within the field of view in the scene. Information about "surface geometry" which is important for, say, three-dimensional object recognition is more easily extracted from "2 1/2 D" range images than from "2D" intensity images. As a result, both active sensors such as laser range finders and passive techniques such as multi-camera stereo vision are being increasingly utilized by vision researchers to solve a variety of problems. This book contains chapters written by distinguished computer vision researchers covering the following areas: Overview of 3D Vision Range Sensing Geometric Processing Object Recognition Navigation Inspection Multisensor Fusion A workshop report, written by the editors, also appears in the book. It summarizes the state of the art and proposes future research directions in range image sensing, processing, interpretation, and applications. The book also contains an extensive, up-to-date bibliography on the above topics. This book provides a unique perspective on the problem of three-dimensional sensing and processing; it is the only comprehensive collection of papers devoted to range images. Both academic researchers interested in research issues in 3D vision and industrial engineers in search of solutions to particular problems will find this a useful reference book.

Robotics Research Technical Report

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Author :
Publisher : Forgotten Books
ISBN 13 : 9780267686704
Total Pages : 44 pages
Book Rating : 4.6/5 (867 download)

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Book Synopsis Robotics Research Technical Report by : David G. Lowe

Download or read book Robotics Research Technical Report written by David G. Lowe and published by Forgotten Books. This book was released on 2018-02-03 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Robotics Research Technical Report: Three-Dimensional Object Recognition From Single Two-Dimensional Images Much recent research in computer vision has been aimed at the reconstruction of depth information from the two-dimensional visual input. An assumption underlying some of this research is that the recognition of three-dimensional objects can most easily be carried out by matching against reconstructed three-dimensional data. However, there is reason to believe that this is not the primary pathway used for recognition in human vision and that most practical applications of computer vision could similarly be performed without bottom-up depth reconstruction. Although depth measurement has an important role in certain visual problems, it is often unavailable or is expensive to obtain. General-purpose vision must be able to function effectively even in the absence of the extensive information required for bottom-up reconstruction of depth or other physical properties. In fact, humanvision does function very well at recognizing images, such as simple line drawings, that lack any reliable clues for the reconstruction of depth prior to recognition. This capability also parallels many other areas in which human vision can make use of partial and locally ambiguous information to achieve reliable identifications. This paper presents several methods for bridging the gap between two - dimensional images and knowledge of three dimensional objects without any preliminary derivation of depth. Of equal importance, these methods address the critical problem of robustness, with the ability to function in spite of missing data, occlusion, and many forms of image degradation. How is it possible to recognize an object from its two-dimensional projection when we have no prior knowledge of the viewpoint from which we will be seeing it? An important role is played by the process of perceptual organization, which detects groupings and structures in the image that are likely to be invariant over wide ranges of viewpoints. While it is true that the appearance of a three-dimensional object can change completely as it is viewed from different viewpoints, it is also true that many aspects of an object's projection remain invariant over large ranges of viewpoints (examples include instances of connectivity, collinearity, parallelism, texture properties, and certain symmetries). It is the role of perceptual organization to detect those image groupings that are unlikely to have arisen by accident of viewpoint or position. Once detected, these groupings can be matched to corresponding structures in the objects through a knowledge-based matching process. It is possible to use probabilistic reasoning to rank the potential matches in terms of their predicted reliability, thereby focusing the search on the most reliable evidence present in a particular image. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

From Surfaces to Objects

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Publisher :
ISBN 13 :
Total Pages : 314 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis From Surfaces to Objects by : R. B. Fisher

Download or read book From Surfaces to Objects written by R. B. Fisher and published by . This book was released on 1989-06-07 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified approach to the theory and practice of computer vision. Presents a model-based, 3-dimensional scene analysis that combines surface patches segmented from the 3-dimensional scene description; surface-patch-based object models; a hierarchy of representations, models, and recognitions; a distributed-network-based model invocation process; and a knowledge-based model matcher. Describes the model-independent scene analysis, and how objects are represented and selected, and shows how to locate, verify, and understand a known object given its geometric model.

Three-dimensional Object Recognition Using an Unsupervised Neural Network

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Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (48 download)

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Book Synopsis Three-dimensional Object Recognition Using an Unsupervised Neural Network by :

Download or read book Three-dimensional Object Recognition Using an Unsupervised Neural Network written by and published by . This book was released on 1992 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Toward Category-Level Object Recognition

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Author :
Publisher : Springer
ISBN 13 : 3540687955
Total Pages : 622 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Toward Category-Level Object Recognition by : Jean Ponce

Download or read book Toward Category-Level Object Recognition written by Jean Ponce and published by Springer. This book was released on 2007-01-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.

Object Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 1447137221
Total Pages : 352 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Object Recognition by : M. Bennamoun

Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.

3D Computer Vision

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1447141504
Total Pages : 390 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis 3D Computer Vision by : Christian Wöhler

Download or read book 3D Computer Vision written by Christian Wöhler and published by Springer Science & Business Media. This book was released on 2012-07-23 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable text introduces the foundations of three-dimensional computer vision and describes recent contributions to the field. Fully revised and updated, this much-anticipated new edition reviews a range of triangulation-based methods, including linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and flexible objects. Also covered are intensity-based techniques that evaluate the pixel grey values in the image to infer three-dimensional scene structure, and point spread function based approaches that exploit the effect of the optical system. The text shows how methods which integrate these concepts are able to increase reconstruction accuracy and robustness, describing applications in industrial quality inspection and metrology, human-robot interaction, and remote sensing.