Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Author: Peter Sturm

Publisher: Now Publishers Inc

Published: 2011

Total Pages: 194

ISBN-13: 1601984103

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Camera Models and Fundamental Concepts Used in Geometric Computer Vision surveys the image acquisition methods used in computer vision and especially, of the vast number of camera models that have been proposed and investigated over the years, and points out similarities between different models.


Computer Vision -- ACCV 2014

Computer Vision -- ACCV 2014

Author: Daniel Cremers

Publisher: Springer

Published: 2015-04-15

Total Pages: 743

ISBN-13: 3319168657

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The five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.


Feature Extraction and Image Processing for Computer Vision

Feature Extraction and Image Processing for Computer Vision

Author: Mark Nixon

Publisher: Academic Press

Published: 2019-11-17

Total Pages: 652

ISBN-13: 0128149779

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Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. - The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods - A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning - Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) - Good balance between providing a mathematical background and practical implementation - Detailed and explanatory of algorithms in MATLAB and Python


Omnidirectional Vision

Omnidirectional Vision

Author: Pascal Vasseur

Publisher: John Wiley & Sons

Published: 2024-01-11

Total Pages: 260

ISBN-13: 1789451434

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Omnidirectional cameras, vision sensors that can capture 360° images, have in recent years had growing success in computer vision, robotics and the entertainment industry. In fact, modern omnidirectional cameras are compact, lightweight and inexpensive, and are thus being integrated in an increasing number of robotic platforms and consumer devices. However, the special format of output data requires tools that are appropriate for camera calibration, signal analysis and image interpretation. This book is divided into six chapters written by world-renowned scholars. In a rigorous yet accessible way, the mathematical foundation of omnidirectional vision is presented, from image geometry and camera calibration to image processing for central and non-central panoramic systems. Special emphasis is given to fisheye cameras and catadioptric systems, which combine mirrors with lenses. The main applications of omnidirectional vision, including 3D scene reconstruction and robot localization and navigation, are also surveyed. Finally, the recent trend towards AI-infused methods (deep learning architectures) and other emerging research directions are discussed.


Computer Vision -- ACCV 2012

Computer Vision -- ACCV 2012

Author: Kyoung Mu Lee

Publisher: Springer

Published: 2013-03-27

Total Pages: 683

ISBN-13: 3642374476

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The four-volume set LNCS 7724--7727 constitutes the thoroughly refereed post-conference proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012, held in Daejeon, Korea, in November 2012. The total of 226 contributions presented in these volumes was carefully reviewed and selected from 869 submissions. The papers are organized in topical sections on object detection, learning and matching; object recognition; feature, representation, and recognition; segmentation, grouping, and classification; image representation; image and video retrieval and medical image analysis; face and gesture analysis and recognition; optical flow and tracking; motion, tracking, and computational photography; video analysis and action recognition; shape reconstruction and optimization; shape from X and photometry; applications of computer vision; low-level vision and applications of computer vision.


Computer Vision

Computer Vision

Author: Simon J. D. Prince

Publisher: Cambridge University Press

Published: 2012-06-18

Total Pages: 599

ISBN-13: 1107011795

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A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.


Machine Vision Algorithms and Applications

Machine Vision Algorithms and Applications

Author: Carsten Steger

Publisher: John Wiley & Sons

Published: 2017-11-07

Total Pages: 280

ISBN-13: 3527812903

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The second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.


Omnidirectional Stereo Vision for Autonomous Vehicles

Omnidirectional Stereo Vision for Autonomous Vehicles

Author: Schoenbein, Miriam

Publisher: KIT Scientific Publishing

Published: 2015-04-22

Total Pages: 156

ISBN-13: 3731503573

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Environment perception with cameras is an important requirement for many applications for autonomous vehicles and robots. This work presents a stereoscopic omnidirectional camera system for autonomous vehicles which resolves the problem of a limited field of view and provides a 360° panoramic view of the environment. We present a new projection model for these cameras and show that the camera setup overcomes major drawbacks of traditional perspective cameras in many applications.


Multiple View Geometry in Computer Vision

Multiple View Geometry in Computer Vision

Author: Richard Hartley

Publisher: Cambridge University Press

Published: 2004-03-25

Total Pages: 676

ISBN-13: 1139449141

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A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.