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Metric Invariants for Camera Calibration: Designing algorithms from algebraic rank analysis - Brossura
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Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework.
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L'autore
Jun-Sik KIM: Ph.D. in Electrical Engineering (2006) from KAIST, South Korea; Project Scientist at the Robotics Institute, Carnegie Mellon University, USA. In So KWEON: Ph.D. in Robotics (1990) from Carnegie Mellon University, USA; Professor at KAIST, South Korea; Director of the P3DigiCar research center; Editorial board member of IJCV.
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Metric Invariants for Camera Calibration
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LAP LAMBERT Academic Publishing Okt 2011, 2011
ISBN 10: 3846509884
ISBN 13: 9783846509883
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework. 196 pp. Englisch. Codice articolo 9783846509883
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kim Jun-SikJun-Sik KIM: Ph.D. in Electrical Engineering (2006) from KAIST, South Korea Project Scientist at the Robotics Institute, Carnegie Mellon University, USA. In So KWEON: Ph.D. in Robotics (1990) from Carnegie Mellon Univers. Codice articolo 5495584
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Metric Invariants for Camera Calibration : Designing algorithms from algebraic rank analysis
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846509884
ISBN 13: 9783846509883
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework. Codice articolo 9783846509883
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Metric Invariants for Camera Calibration
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Metric Invariants for Camera Calibration
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ISBN 10: 3846509884
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch. Codice articolo 9783846509883
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Metric Invariants for Camera Calibration: Designing algorithms from algebraic rank analysis
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ISBN 10: 3846509884
ISBN 13: 9783846509883
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