[PDF] Computer Analysis Of Scences Of 3 Dimensional Curved Objects eBook

Author : NEVATIA
Publisher : Birkhäuser
Page : 134 pages
File Size : 23,63 MB
Release : 2013-12-20
Category : Science
ISBN : 3034852061

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1.0 2 The attention then turned to the problem of "Body separation", i.e. separation of occluding bodies in a scene (See [Guzman), [Falk), and [Waltz)). Grape ([Grape)) combined the separation of bodies with recognition, by removing parts of the scene recognized as belonging to a known body. All of these techniques were designed to work with polyhedral objects only, and extensively use the properties of edges and vertices. Though some impressive results have been reported ([Waltz], [Grape)), and perhaps some useful abstractions can be made, the specific techniques used fail to generalize to a wider class of objects. Among previous work on curved objects, B.K.P. Horn ([Horn)) presented techniques for extracting three dimensional depth data from a TV image, using reflection characteristics of the surface. Krakauer ([Krakauer]) represented objects by connections of brightness contours. Ambler et al ([Ambler)) describe experiments with simple shapes, including curved objects, using relations within a two-dimensional image. However, none of these efforts really addresses the problem of "shape" representation and description. Work on outdoor scene analysis is also concerned with non-polyhedral objects ([Bajcsy], [Yakimovsky]), but again no attention has been paid to shape analysis.

Author : R. B. Fisher
Publisher :
Page : 314 pages
File Size : 34,5 MB
Release : 1989-06-07
Category : Computers
ISBN :

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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.

Author : Martin Weinmann
Publisher : Springer
Page : 250 pages
File Size : 50,98 MB
Release : 2016-03-17
Category : Computers
ISBN : 3319292463

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This unique work presents a detailed review of the processing and analysis of 3D point clouds. A fully automated framework is introduced, incorporating each aspect of a typical end-to-end processing workflow, from raw 3D point cloud data to semantic objects in the scene. For each of these components, the book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the-art techniques. Topics and features: reviews techniques for the acquisition of 3D point cloud data and for point quality assessment; explains the fundamental concepts for extracting features from 2D imagery and 3D point cloud data; proposes an original approach to keypoint-based point cloud registration; discusses the enrichment of 3D point clouds by additional information acquired with a thermal camera, and describes a new method for thermal 3D mapping; presents a novel framework for 3D scene analysis.

Author : C. Adolfo Guzman-Arenas
Publisher :
Page : 296 pages
File Size : 38,34 MB
Release : 1968
Category : Optical pattern recognition
ISBN :

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Methods are presented: (1) to partition or decompose a visual scene into the bodies forming it; (2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; (3) to find the regions or zones of a visual scene that belong to its background; (4) to carry out the isolation of objects in (1) when the input has inaccuracies. Running computer programs implement the methods, and many examples illustrate their behavior. The input is a two-dimensional line-drawing of the scene, assumed to contain three-dimensional bodies possessing flat faces (polyhedra); some of them may be partially occluded. Suggestions are made for extending the work to curved objects. Some comparisons are made with human visual perception. The main conclusion is that it is possible to sseparate a picture or scene into the constituent objects exclusively in basis of monocular geometric properties (in basis of pure form); in fact, successful methods are shown. (Author).

Author : Herbert Freeman
Publisher : Elsevier
Page : 432 pages
File Size : 16,27 MB
Release : 2012-12-02
Category : Technology & Engineering
ISBN : 0323150632

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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.

Author : T. S. Huang
Publisher : Springer Science & Business Media
Page : 759 pages
File Size : 49,82 MB
Release : 2012-12-06
Category : Computers
ISBN : 3642819354

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This volume contains the proceedings of the NATO Advanced Study Institute on "Image Sequence Processing and Dynamic Scene Analysis" held 21 June - 2 July, 1982 in Hotel Maritim, Braunlage/Harz, Federal Republic of Germany. The organizing eommittee of the institute consists of T.S. Huang (Director), H.G. Musmann (Co Director), H.H. Nagel (Consultant), and C.E. Liedtke and W. Geuen (Local 'arrangement). This Institute was devoted to the rapidly emerging field of image sequence processing and dynamic scene analysis which has man! important applications in cluding target tracking, television bandwidth compression, highway traffic moni toring, and analysis of heart wall motion for medical diagnosis. The lectures and discussions in this Institute fell into three overlapping categories: Motion estimation; pattern recognition and artificial intelligence techniques in dynamic scene analysis; and, applications. 1) Motion estimation - One of the most important problems in image sequence analysis and dynamic scene analysis is displacement and motion estimation. For example, in interframe coding using temporal DPCM, displacement estimation and compensation can improve efficiency significantly. Also, estimated motion parameters can be powerful cues in target segmentation, detection, and classification. In this Institute, a number of recently developed techniques for displacement and motion estimation were discussed.

Author : Martin A. Fischler
Publisher : Elsevier
Page : 815 pages
File Size : 30,72 MB
Release : 2014-06-28
Category : Computers
ISBN : 0080515819

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The field of computer vision combines techniques from physics, mathematics, psychology, artificial intelligence, and computer science to examine how machines might construct meaningful descriptions of their surrounding environment. The editors of this volume, prominent researchers and leaders of the SRI International AI Center Perception Group, have selected sixty papers, most published since 1980, with the viewpoint that computer vision is concerned with solving seven basic problems: Reconstructing 3D scenes from 2D images Decomposing images into their component parts Recognizing and assigning labels to scene objects Deducing and describing relations among scene objects Determining the nature of computer architectures that can support the visual function Representing abstractions in the world of computer memory Matching stored descriptions to image representation Each chapter of this volume addresses one of these problems through an introductory discussion, which identifies major ideas and summarizes approaches, and through reprints of key research papers. Two appendices on crucial assumptions in image interpretation and on parallel architectures for vision applications, a glossary of technical terms, and a comprehensive bibliography and index complete the volume.

Author : Hamid Laga
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 27,17 MB
Release : 2019-01-07
Category : Mathematics
ISBN : 1119405106

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An in-depth description of the state-of-the-art of 3D shape analysis techniques and their applications This book discusses the different topics that come under the title of "3D shape analysis". It covers the theoretical foundations and the major solutions that have been presented in the literature. It also establishes links between solutions proposed by different communities that studied 3D shape, such as mathematics and statistics, medical imaging, computer vision, and computer graphics. The first part of 3D Shape Analysis: Fundamentals, Theory, and Applications provides a review of the background concepts such as methods for the acquisition and representation of 3D geometries, and the fundamentals of geometry and topology. It specifically covers stereo matching, structured light, and intrinsic vs. extrinsic properties of shape. Parts 2 and 3 present a range of mathematical and algorithmic tools (which are used for e.g., global descriptors, keypoint detectors, local feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D objects. Both also place strong emphasis on recent techniques motivated by the spread of commodity devices for 3D acquisition. Part 4 demonstrates the use of these techniques in a selection of 3D shape analysis applications. It covers 3D face recognition, object recognition in 3D scenes, and 3D shape retrieval. It also discusses examples of semantic applications and cross domain 3D retrieval, i.e. how to retrieve 3D models using various types of modalities, e.g. sketches and/or images. The book concludes with a summary of the main ideas and discussions of the future trends. 3D Shape Analysis: Fundamentals, Theory, and Applications is an excellent reference for graduate students, researchers, and professionals in different fields of mathematics, computer science, and engineering. It is also ideal for courses in computer vision and computer graphics, as well as for those seeking 3D industrial/commercial solutions.

Author : Derek Hoiem
Publisher : Morgan & Claypool Publishers
Page : 172 pages
File Size : 35,53 MB
Release : 2011
Category : Computers
ISBN : 1608457281

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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