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" Theory of Reconstruction from Image Motion "
by Stephen Maybank.
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BL
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| Record Number
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753725
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b573686
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| Main Entry
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by Stephen Maybank.
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| Title & Author
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Theory of Reconstruction from Image Motion\ by Stephen Maybank.
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| Publication Statement
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Berlin, Heidelberg : Springer Berlin Heidelberg, 1993
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| Series Statement
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Springer series in information sciences, 28.
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| Page. NO
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(xi, 261 pages 29 illustrations)
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| ISBN
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3540555374
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: 3642775578
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: 9783540555377
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: 9783642775574
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| Contents
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1 Introduction --; 1.1 Background --; 1.2 Reconstruction --; 1.3 Conventions About the Image --; 1.4 Mathematical Background --; References --; 2 Reconstruction from Image Correspondences --; 2.1 Euclidean Framework for Reconstruction --; 2.2 Essential Matrices --; 2.3 Projective Framework for Reconstruction --; 2.4 Reconstruction up to a Collineation --; References --; 3 Critical Surfaces and Horopter Curves --; 3.1 The Absolute Conic --; 3.2 Rectangular Quadrics --; 3.3 Horopter Curves --; 3.4 Horopter Curves and Reconstruction --; 3.5 Reconstruction up to a Collineation --; References --; 4 Reconstruction from Image Velocities --; 4.1 Framework --; 4.2 Ambiguity --; 4.3 Algebraic Properties of Four Image Velocity Vectors --; 4.4 The Linear System of Quartics --; 4.5 The Derivatives of the Image Velocity Field --; References --; 5 Reconstruction from Minimal Data --; 5.1 Kruppa's Method --; 5.2 Demazure's Method --; 5.3 Reconstruction up to a Collineation --; 5.4 Reconstruction From Five Image Velocity Vectors --; References --; 6 Algorithms --; 6.1 Reconstruction from Image Correspondences --; 6.2 Reconstruction from Image Velocities --; References.
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| Abstract
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Theory of Reconstruction from Image Motion presents the mathematics underlying the reconstruction of camera motion from the movements of points in the camera image. It describes recent work employing mathematical methodsdrawn from linear algebra, projective geometry, algebraic geometry, the theory of transversality and the theory of least squares approximation. Manyproblems in reconstruction are best tackled using methods from projective oralgebraic geometry. However, these methods are not widely known to researchers in computer vision. As a consequence, purely algebraic methods are often used instead, leading to large and complicated expressions, which are difficult to interpret. Many of the arguments in thisvolume illustrate the speed and efficiency of geometric methods for solving certain problems that arise in reconstruction. This book is a good starting point for anyone interested in the application of different mathematical techniques to the rapidly expanding field of computer vision, especially in the areas of vehicle guidance, robotics and remote sensing.
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Computer simulation.
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Mathematical physics.
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Physics.
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| LC Classification
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TA1632.B978 1993
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| Added Entry
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Stephen Maybank
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