Representations And Techniques For 3d Object Recognition And Scene Interpretation

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Representations and Techniques for 3D Object Recognition and Scene Interpretation

Derek Hoiem,Silvio Savarese
Representations and Techniques for 3D Object Recognition and Scene Interpretation Book PDF

Author : Derek Hoiem,Silvio Savarese
Publisher : Morgan & Claypool Publishers
Page : 171 pages
File Size : 48,7 Mb
Release : 2011-09-09
Category : Technology & Engineering
ISBN : 9781608457298

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Representations and Techniques for 3D Object Recognition and Scene Interpretation by Derek Hoiem,Silvio Savarese Pdf

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

Derek Santhanam,Silvio Basu
Representations and Techniques for 3D Object Recognition and Scene Interpretation Book PDF

Author : Derek Santhanam,Silvio Basu
Publisher : Springer Nature
Page : 147 pages
File Size : 44,8 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031015571

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Representations and Techniques for 3D Object Recognition and Scene Interpretation by Derek Santhanam,Silvio Basu Pdf

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

3D Shape Analysis

Hamid Laga,Yulan Guo,Hedi Tabia,Robert B. Fisher,Mohammed Bennamoun
3D Shape Analysis Book PDF

Author : Hamid Laga,Yulan Guo,Hedi Tabia,Robert B. Fisher,Mohammed Bennamoun
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 51,6 Mb
Release : 2019-01-07
Category : Mathematics
ISBN : 9781119405108

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3D Shape Analysis by Hamid Laga,Yulan Guo,Hedi Tabia,Robert B. Fisher,Mohammed Bennamoun Pdf

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.

Machine Vision for Three-Dimensional Scenes

Herbert Freeman
Machine Vision for Three Dimensional Scenes Book PDF

Author : Herbert Freeman
Publisher : Elsevier
Page : 432 pages
File Size : 48,8 Mb
Release : 2012-12-02
Category : Technology & Engineering
ISBN : 9780323150637

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Machine Vision for Three-Dimensional Scenes by Herbert Freeman Pdf

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.

Graph Representation Learning

William L. William L. Hamilton
Graph Representation Learning Book PDF

Author : William L. William L. Hamilton
Publisher : Springer Nature
Page : 141 pages
File Size : 42,7 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031015885

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Graph Representation Learning by William L. William L. Hamilton Pdf

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Advances in Visual Computing

George Bebis,Richard Boyle,Bahram Parvin,Darko Koracin,Fatih Porikli,Sandra Skaff,Alireza Entezari,Jianyuan Min,Daisuke Iwai,Amela Sadagic,Carlos Scheidegger,Tobias Isenberg
Advances in Visual Computing Book PDF

Author : George Bebis,Richard Boyle,Bahram Parvin,Darko Koracin,Fatih Porikli,Sandra Skaff,Alireza Entezari,Jianyuan Min,Daisuke Iwai,Amela Sadagic,Carlos Scheidegger,Tobias Isenberg
Publisher : Springer
Page : 631 pages
File Size : 53,5 Mb
Release : 2016-12-09
Category : Computers
ISBN : 9783319508320

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Advances in Visual Computing by George Bebis,Richard Boyle,Bahram Parvin,Darko Koracin,Fatih Porikli,Sandra Skaff,Alireza Entezari,Jianyuan Min,Daisuke Iwai,Amela Sadagic,Carlos Scheidegger,Tobias Isenberg Pdf

The two volume set LNCS 10072 and LNCS 10073 constitutes the refereed proceedings of the 12th International Symposium on Visual Computing, ISVC 2016, held in Las Vegas, NV, USA in December 2016. The 102 revised full papers and 34 poster papers presented in this book were carefully reviewed and selected from 220 submissions. The papers are organized in topical sections: Part I (LNCS 10072) comprises computational bioimaging; computer graphics; motion and tracking; segmentation; pattern recognition; visualization; 3D mapping; modeling and surface reconstruction; advancing autonomy for aerial robotics; medical imaging; virtual reality; computer vision as a service; visual perception and robotic systems; and biometrics. Part II (LNCS 9475): applications; visual surveillance; computer graphics; and virtual reality.

Outils d’analyse vidéo : pour une pleine exploitation des données de la vidéoprotection

DUFOUR Jean-Yves
Outils d analyse vid o pour une pleine exploitation des donn es de la vid oprotection Book PDF

Author : DUFOUR Jean-Yves
Publisher : Lavoisier
Page : 386 pages
File Size : 46,5 Mb
Release : 2012-10-22
Category : Electronic
ISBN : 9782746288904

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Outils d’analyse vidéo : pour une pleine exploitation des données de la vidéoprotection by DUFOUR Jean-Yves Pdf

L’utilisation croissante de la vidéoprotection rend nécessaire la mise en place de fonctions d’analyse vidéo pour alléger voire automatiser des tâches aujourd’hui entièrement réalisées par des opérateurs. Après avoir dressé un panorama des avancées et des perspectives en analyse d’image, cet ouvrage détaille les principales fonctions d’analyse vidéo, comme la détection, le suivi et la reconnaissance d’objets d’intérêt (personnes ou véhicules) ou les fonctions de « haut-niveau » visant à interpréter les scènes observées (évènements, comportements, nature de la scène...). Les besoins sont illustrés sous l’angle de deux applications majeures, la sécurité des transports et l’investigation. Les contraintes d’ordres juridique et éthique sont présentées, ainsi que les caractéristiques des données vidéo traitées, au travers des caméras et des méthodes de compression utilisées. La problématique de l’évaluation de performance, tant au niveau opérationnel qu’au niveau des fonctions d’analyse, est également exposée.

A Concise Introduction to Models and Methods for Automated Planning

Hector Radanovic
A Concise Introduction to Models and Methods for Automated Planning Book PDF

Author : Hector Radanovic
Publisher : Springer Nature
Page : 132 pages
File Size : 42,9 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031015649

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A Concise Introduction to Models and Methods for Automated Planning by Hector Radanovic Pdf

Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective. Table of Contents: Preface / Planning and Autonomous Behavior / Classical Planning: Full Information and Deterministic Actions / Classical Planning: Variations and Extensions / Beyond Classical Planning: Transformations / Planning with Sensing: Logical Models / MDP Planning: Stochastic Actions and Full Feedback / POMDP Planning: Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography

Intelligent Systems

Cornelius T. Leondes
Intelligent Systems Book PDF

Author : Cornelius T. Leondes
Publisher : CRC Press
Page : 2400 pages
File Size : 53,6 Mb
Release : 2018-10-08
Category : Technology & Engineering
ISBN : 9781420040814

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Intelligent Systems by Cornelius T. Leondes Pdf

Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study examples of successful practical techniques and solutions for diverse applications ranging from robotic systems to speech and signal processing, database management, and manufacturing.

Analysis and Interpretation of Range Images

Ramesh C. Jain,Anil K. Jain
Analysis and Interpretation of Range Images Book PDF

Author : Ramesh C. Jain,Anil K. Jain
Publisher : Springer Science & Business Media
Page : 393 pages
File Size : 40,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461233602

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Analysis and Interpretation of Range Images by Ramesh C. Jain,Anil K. Jain Pdf

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.

3D Imaging, Analysis and Applications

Yonghuai Liu,Nick Pears,Paul L. Rosin,Patrik Huber
3D Imaging Analysis and Applications Book PDF

Author : Yonghuai Liu,Nick Pears,Paul L. Rosin,Patrik Huber
Publisher : Springer Nature
Page : 736 pages
File Size : 41,9 Mb
Release : 2020-09-11
Category : Computers
ISBN : 9783030440701

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3D Imaging, Analysis and Applications by Yonghuai Liu,Nick Pears,Paul L. Rosin,Patrik Huber Pdf

This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops. Overall, the book covers three main areas: ● 3D imaging, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation; ● 3D shape analysis, including local descriptors, registration, matching, 3D morphable models, and deep learning on 3D datasets; and ● 3D applications, including 3D face recognition, cultural heritage and 3D phenotyping of plants. 3D computer vision is a rapidly advancing area in computer science. There are many real-world applications that demand high-performance 3D imaging and analysis and, as a result, many new techniques and commercial products have been developed. However, many challenges remain on how to analyse the captured data in a way that is sufficiently fast, robust and accurate for the application. Such challenges include metrology, semantic segmentation, classification and recognition. Thus, 3D imaging, analysis and their applications remain a highly-active research field that will continue to attract intensive attention from the research community with the ultimate goal of fully automating the 3D data capture, analysis and inference pipeline.

Object Representation in Computer Vision II

Jean Ponce,Andrew Zisserman
Object Representation in Computer Vision II Book PDF

Author : Jean Ponce,Andrew Zisserman
Publisher : Springer Science & Business Media
Page : 422 pages
File Size : 51,6 Mb
Release : 1996-09-25
Category : Computers
ISBN : 3540617507

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Object Representation in Computer Vision II by Jean Ponce,Andrew Zisserman Pdf

This book constitutes the strictly refereed post-workshop proceedings of the second International Workshop on Object Representation in Computer Vision, held in conjunction with ECCV '96 in Cambridge, UK, in April 1996. The 15 revised full papers contained in the book were selected from 45 submissions for presentation at the workshop. Also included are three invited contributions based on the talks by Takeo Kanade, Jan Koenderink, and Ram Nevatia as well as a workshop report by the volume editors summarizing several panel discussions and the general state of the art in the area.

3D Dynamic Scene Analysis

Zhengyou Zhang,Olivier Faugeras
3D Dynamic Scene Analysis Book PDF

Author : Zhengyou Zhang,Olivier Faugeras
Publisher : Springer Science & Business Media
Page : 0 pages
File Size : 41,6 Mb
Release : 1992
Category : Computer vision
ISBN : 3540554297

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3D Dynamic Scene Analysis by Zhengyou Zhang,Olivier Faugeras Pdf

1. Introduction.- 1.1 Brief Overview of Motion Analysis.- 1.2 Statement of the "Motion from Stereo" Problem.- 1.3 Organization of The Book.- 2. Uncertainty Manipulation and Parameter Estimation.- 2.1 Probability Theory and Geometric Probability.- 2.2 Parameter Estimation.- 2.2.1 Standard Kalman filter.- 2.2.2 Extended Kalman filter.- 2.2.3 Discussion.- 2.2.4 Iterated ExtendKalman Filter.- 2.2.5 Robustness and Confidence Procedure.- 2.3 Summary.- 2.4 Appendix: Least-Squares Techniques.- 3. Reconstruction of 3D Line Segments.- 3.1 Why 3D Line Segments.- 3.2 Stereo Calibration.- 3.2.1 Camera Calibration.- 3.2.2 Epipolar Constraint.- 3.3 Algorithm of the Trinocular Stereovision.- 3.4 Reconstruction of 3D Segments.- 3.5 Summary.- 4. Representations of Geometric Objects.- 4.1 Rigid Motion.- 4.1.1 Definition.- 4.1.2 Representations.- 4.2 3D Line Segments.- 4.2.1 Previous Representations and Deficiencies.- 4.2.2 A New Representation.- 4.3 Summary.- 4.4 Appendix: Visualizing Uncertainty.- 5. A Comparative Study of 3D Motion Estimation.- 5.1 Problem Statement.- 5.1.1 Line Segment Representations.- 5.1.2 3D Line Segment Transformation.- 5.2 Extended Kalman Filter Approaches.- 5.2.1 Linearization of the Equations.- 5.2.2 Derivation of Rotation Matrix.- 5.3 Minimization Techniques.- 5.4 Analytical Solution.- 5.4.1 Determining the Rotation.- 5.4.2 Determining the Translation.- 5.5 Kim and Aggarwal's method.- 5.5.1 Determining the Rotation.- 5.5.2 Determining the Translation.- 5.6 Experimental Results.- 5.6.1 Results with Synthetic Data.- 5.6.2 Results with Real Data.- 5.7 Summary.- 5.8 Appendix: Motion putation Using the New Line Segment Representation.- 6. Matching and Rigidity Constraints.- 6.1 Matching as a Search.- 6.2 Rigidity Constraint.- 6.3 Completeness of the Rigidity Constraints.- 6.4 Error Measurements inn the Constraints.- 6.4.1 Norm Constraint.- 6.4.2 Dot-Product Constraint.- 6.4.3 Triple-Product Constraint.- 6.5 Other Formalisms Rigidity Constraints.- 6.6 Summary.- 7. Hypothesize-and-Verify Method for Two 3D View Motion Analysis.- 7.1 General Presentation.- 7.1.1 Search in the Transformation Space.- 7.1.2 Hypothesize-and-Verify Method.- 7.2 Generating Hypotheses.- 7.2.1 Definition and Primary Algorithm.- 7.2.2 Control Strates in Hypothesis Generation.- 7.2.3 Additional Constraints.- 7.2.4 Algorithm of Hypothesis Generation.- 7.3 Verifying Hypothesis.- 7.3.1 Estimating the Initial Rigid Motion.- 7.3.2 Propagating Hyphoteses.- 7.3.3 Choosing the Best Hypothesis.- 7.3.4 Algorithm of Hypothesis Verification.- 7.4 Matching Noisy Segments.- 7.4.1 Version 1.- 7.4.2 Version 2.- 7.4.3 Version 3.- 7.5 Experimental Results.- 7.5.1 Indoor Scenes with a Large Common Part.- 7.5.2 Indoor Scenes with a Small Common Part.- 7.5.3 Rock Scenes.- 7.6 Summary.- 7.7 Appendix: Transforming a 3D Line Segment.- 8. Further Considerations on Reducing Complexity.- 8.1 Sorting Data Features.- 8.2 "Good-Enough" Method.- 8.3 Speeding Up the Hypothesis Generation Process Through Grouping.- 8.4 Finding Clusters Based on Proximity.- 8.5 Finding Planes.- 8.6 Experimental Results.- 8.6.1 Grouping Results.- 8.6.2 Motion Results.- 8.7 Conclusion.- 9. Multiple Object Motions.- 9.1 Multiple Object Motions.- 9.2 Influence of Egomotion on Observed Object Motion.- 9.3 Experimental Results.- 9.3.1 Real Scene with Synthetic Moving Objects.- 9.3.2 Real Scene with a Real Moving Object.- 9.4 Summary.- 10. Object Recognition and Localization.- 10.1 Model-Based Object Recognition.- 10.2 Adapting the Motion-Determination Algorithm.- 10.3 Experimental Result.- 10.4 Summary.- 11. Calibrating a Mobile Robot and Visual Navigation.- 11.1 The INRIA Mobile Robot.- 11.2 Calibration Problem.- 11.3 Navigation Problem.- 11.4 Experimental Results.- 11.5 Integrating Motion Information from Odometry.- 11.6 Summary.- 12. Fusing Multiple 3D Frames.- 12.1 System Description.- 12.2 Fusing Segments from Multiple Views.- 12.2.1 Fusing General Primitives.- 12.2.2 Fusing Line Segments.- 12.2.3 Ex...

Visual Form

C. Arcelli,L.P. Cordella,G.S. di Baja
Visual Form Book PDF

Author : C. Arcelli,L.P. Cordella,G.S. di Baja
Publisher : Springer Science & Business Media
Page : 637 pages
File Size : 48,5 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9781489907158

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Visual Form by C. Arcelli,L.P. Cordella,G.S. di Baja Pdf

This book contains the papers presented at the International Workshop on Visual Fonn, held in Capri (Italy) on May 27-30, 1991. The workshop, sponsored by the International Association for Pattern Recognition (!APR), has been jointly organized by the Dipartimento di Infonnatica e Sisternistica of the University of Naples and the Istituto di Cibemetica of the National Research Council of Italy, and has focussed on Shape. Shape is a distinctive feature of most patterns, so that recognition can often be attained through shape discrimination. The organizers of the workshop shared the general feeling manifested by researchers, that it was time for holding a meeting exclusively devoted to a feature so crucial for both human and machine perception. During this meeting, problems and prospects in the field of 2D and 3D shape analysis could be discussed extensively, so as to provide an effective, updated picture of the current research activity in which shape plays a central role. Indeed, many highly qualified researchers in the field positively reacted to the Call for Papers.

Describing and Recognizing 3-D Objects Using Surface Properties

Ting-Jun Fan
Describing and Recognizing 3 D Objects Using Surface Properties Book PDF

Author : Ting-Jun Fan
Publisher : Springer Science & Business Media
Page : 150 pages
File Size : 42,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461244660

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Describing and Recognizing 3-D Objects Using Surface Properties by Ting-Jun Fan Pdf

Surface properties play a very important role in many perception tasks. Object recognition, navigation, and inspection use surface properties ex tensively. Characterizing surfaces at different scales in given data is often the first and possibly the most important step. Most early research in ma chine perception relied on only very coarse characterization of surfaces. In the last few years, surface characterization has been receiving due attention. Dr. T. J. Fan is one of the very few researchers who designed and im plemented a complete system for object recognition. He studied issues re lated to characterization of surfaces in the context of object recognition, and then uses the features thus developed for recognizing objects. He uses a multi-view representation of 3-D objects for recognition, and he devel ops techniques for the segmentation of range images to obtain features for recognition. His matching approach also allows him to recognize objects from their partial views in the presence of other occluding objects. The efficacy of his approach is demonstrated in many examples.