Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds

Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds

Author: Vladislav Golyanik

Publisher: Springer Nature

Published: 2020-06-04

Total Pages: 352

ISBN-13: 3658305673

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Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book. About the Author: Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras).


Book Synopsis Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds by : Vladislav Golyanik

Download or read book Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds written by Vladislav Golyanik and published by Springer Nature. This book was released on 2020-06-04 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book. About the Author: Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras).

Pattern Recognition

Pattern Recognition

Author: Zeynep Akata

Publisher: Springer Nature

Published: 2021-03-16

Total Pages: 504

ISBN-13: 3030712788

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This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic. The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.


Book Synopsis Pattern Recognition by : Zeynep Akata

Download or read book Pattern Recognition written by Zeynep Akata and published by Springer Nature. This book was released on 2021-03-16 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic. The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.

Deformable Surface 3D Reconstruction from Monocular Images

Deformable Surface 3D Reconstruction from Monocular Images

Author: Amit Roy-Chowdhury

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 99

ISBN-13: 3031018109

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Being able to recover the shape of 3D deformable surfaces from a single video stream would make it possible to field reconstruction systems that run on widely available hardware without requiring specialized devices. However, because many different 3D shapes can have virtually the same projection, such monocular shape recovery is inherently ambiguous. In this survey, we will review the two main classes of techniques that have proved most effective so far: The template-based methods that rely on establishing correspondences with a reference image in which the shape is already known, and non-rigid structure-from-motion techniques that exploit points tracked across the sequences to reconstruct a completely unknown shape. In both cases, we will formalize the approach, discuss its inherent ambiguities, and present the practical solutions that have been proposed to resolve them. To conclude, we will suggest directions for future research. Table of Contents: Introduction / Early Approaches to Non-Rigid Reconstruction / Formalizing Template-Based Reconstruction / Performing Template-Based Reconstruction / Formalizing Non-Rigid Structure from Motion / Performing Non-Rigid Structure from Motion / Future Directions


Book Synopsis Deformable Surface 3D Reconstruction from Monocular Images by : Amit Roy-Chowdhury

Download or read book Deformable Surface 3D Reconstruction from Monocular Images written by Amit Roy-Chowdhury and published by Springer Nature. This book was released on 2022-05-31 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Being able to recover the shape of 3D deformable surfaces from a single video stream would make it possible to field reconstruction systems that run on widely available hardware without requiring specialized devices. However, because many different 3D shapes can have virtually the same projection, such monocular shape recovery is inherently ambiguous. In this survey, we will review the two main classes of techniques that have proved most effective so far: The template-based methods that rely on establishing correspondences with a reference image in which the shape is already known, and non-rigid structure-from-motion techniques that exploit points tracked across the sequences to reconstruct a completely unknown shape. In both cases, we will formalize the approach, discuss its inherent ambiguities, and present the practical solutions that have been proposed to resolve them. To conclude, we will suggest directions for future research. Table of Contents: Introduction / Early Approaches to Non-Rigid Reconstruction / Formalizing Template-Based Reconstruction / Performing Template-Based Reconstruction / Formalizing Non-Rigid Structure from Motion / Performing Non-Rigid Structure from Motion / Future Directions

Deformable Surface 3D Reconstruction from Monocular Images

Deformable Surface 3D Reconstruction from Monocular Images

Author: Mathieu Salzmann

Publisher: Morgan & Claypool Publishers

Published: 2011

Total Pages: 114

ISBN-13: 1608455831

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7. Future directions -- Bibliography -- Authors' biographies.


Book Synopsis Deformable Surface 3D Reconstruction from Monocular Images by : Mathieu Salzmann

Download or read book Deformable Surface 3D Reconstruction from Monocular Images written by Mathieu Salzmann and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: 7. Future directions -- Bibliography -- Authors' biographies.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

Representations and Techniques for 3D Object Recognition and Scene Interpretation

Author: Derek Hoiem

Publisher: Morgan & Claypool Publishers

Published: 2011

Total Pages: 172

ISBN-13: 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


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

RGB-D Image Analysis and Processing

RGB-D Image Analysis and Processing

Author: Paul L. Rosin

Publisher: Springer

Published: 2019-11-06

Total Pages: 524

ISBN-13: 9783030286026

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This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.


Book Synopsis RGB-D Image Analysis and Processing by : Paul L. Rosin

Download or read book RGB-D Image Analysis and Processing written by Paul L. Rosin and published by Springer. This book was released on 2019-11-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.

RoboCup 2019: Robot World Cup XXIII

RoboCup 2019: Robot World Cup XXIII

Author: Stephan Chalup

Publisher: Springer Nature

Published: 2019-11-30

Total Pages: 671

ISBN-13: 303035699X

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This book includes the post-conference proceedings of the 23rd RoboCup International Symposium, held in Sydney, NSW, Australia, in July 2019. The 38 full revised papers and 14 invited papers presented in this book were carefully reviewed and selected from 74 submissions. This book highlights the approaches of champion teams from the competitions and documents the proceedings of the 23rd annual RoboCup International Symposium. Due to the complex research challenges set by the RoboCup initiative, the RoboCup International Symposium offers a unique perspective for exploring scientific and engineering principles underlying advanced robotic and AI systems.


Book Synopsis RoboCup 2019: Robot World Cup XXIII by : Stephan Chalup

Download or read book RoboCup 2019: Robot World Cup XXIII written by Stephan Chalup and published by Springer Nature. This book was released on 2019-11-30 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the post-conference proceedings of the 23rd RoboCup International Symposium, held in Sydney, NSW, Australia, in July 2019. The 38 full revised papers and 14 invited papers presented in this book were carefully reviewed and selected from 74 submissions. This book highlights the approaches of champion teams from the competitions and documents the proceedings of the 23rd annual RoboCup International Symposium. Due to the complex research challenges set by the RoboCup initiative, the RoboCup International Symposium offers a unique perspective for exploring scientific and engineering principles underlying advanced robotic and AI systems.

Monocular Model-based 3D Tracking of Rigid Objects

Monocular Model-based 3D Tracking of Rigid Objects

Author: Vincent Lepetit

Publisher: Now Publishers Inc

Published: 2005

Total Pages: 108

ISBN-13: 9781933019031

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Monocular Model-Based 3D Tracking of Rigid Objects reviews the different techniques and approaches that have been developed by industry and research.


Book Synopsis Monocular Model-based 3D Tracking of Rigid Objects by : Vincent Lepetit

Download or read book Monocular Model-based 3D Tracking of Rigid Objects written by Vincent Lepetit and published by Now Publishers Inc. This book was released on 2005 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monocular Model-Based 3D Tracking of Rigid Objects reviews the different techniques and approaches that have been developed by industry and research.

Computer Vision Metrics

Computer Vision Metrics

Author: Scott Krig

Publisher: Apress

Published: 2014-06-14

Total Pages: 498

ISBN-13: 1430259302

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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 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.

Object Recognition

Object Recognition

Author: M. Bennamoun

Publisher: Springer Science & Business Media

Published: 2001-12-12

Total Pages: 376

ISBN-13: 9781852333980

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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.


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.