Omnidirectional Vision

Pascal Vasseur , Fabio Morbidi 지음

Wiley-ISTE 2023년 12월 12일 출간

작품소개

책소개

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.

목차

Acknowledgments xi List of Acronyms xiii Preface xvFabio MORBIDI and Pascal VASSEUR Chapter 1 Image Geometry 1Peter STURM 1.1 Introduction 2 1.1.1 Outline of this chapter 5 1.2 Image formation and point-wise approximation 6 1.3 Projection and back-projection 7 1.4 Central and non-central cameras 12 1.5 "Outer" geometry: calibrated cameras 16 1.5.1 Given an image of a scene and a particular point in that image, where could the original point in the scene possibly be located? 17 1.5.2 Is it possible to precisely locate an object in 3D from a single image and if yes, what information is required to do so and how do we solve this problem mathematically? 17 1.5.3 Is it possible to estimate the motion of a camera just by taking images of an unknown scene? 19 1.5.4 Triangulation reconstructing 3D points 21 1.5.5 Some remarks 22 1.6 "Inner" geometry: images of lines 24 1.7 Epipolar geometry 26 1.7.1 Nature of epipolar geometry 26 1.7.2 Dense stereo matching and rectification 31 1.8 Conclusion 35 1.9 Acknowledgments 35 1.10 References 36 Chapter 2 Models and Calibration Methods 39Guillaume CARON 2.1 Introduction 39 2.2 Projection models 40 2.2.1 Perspective projection: a review 40 2.2.2 Ad hoc models 43 2.2.3 Unified central projection and its extensions 49 2.2.4 Generic models 54 2.3 Calibration methods 54 2.4 Conclusion 57 2.5 References 59 Chapter 3 Reconstruction of Environments 63Maxime LHUILLIER 3.1 Prerequisites 64 3.1.1 Image rectification and matching constraints 64 3.1.2 From disparity to depth 65 3.1.3 Dynamic programming and semi-global matching methods (SGM) 66 3.1.4 Plane sweeping methods 67 3.1.5 Minimization of global ene

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저자(글) Pascal Vasseur

저자(글) Fabio Morbidi