Open AccessBook
The Geometry of Multiple Images: The Laws That Govern the Formation of Multiple Images of a Scene and Some of Their Applications
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TLDR
The state of knowledge in one subarea of vision is described, the geometric laws that relate different views of a scene from the perspective of various types of geometries, which is a unified framework for thinking about many geometric problems relevant to vision.Abstract:
From the Publisher:
with contributions from Theo Papadopoulo
Over the last forty years, researchers have made great strides in elucidating the laws of image formation, processing, and understanding by animals, humans, and machines. This book describes the state of knowledge in one subarea of vision, the geometric laws that relate different views of a scene. Geometry, one of the oldest branches of mathematics, is the natural language for describing three-dimensional shapes and spatial relations. Projective geometry, the geometry that best models image formation, provides a unified framework for thinking about many geometric problems relevant to vision. The book formalizes and analyzes the relations between multiple views of a scene from the perspective of various types of geometries. A key feature is that it considers Euclidean and affine geometries as special cases of projective geometry.
Images play a prominent role in computer communications. Producers and users of images, in particular three-dimensional images, require a framework for stating and solving problems. The book offers a number of conceptual tools and theoretical results useful for the design of machine vision algorithms. It also illustrates these tools and results with many examples of real applications.read more
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Free Viewpoint Video Synthesis from Uncalibrated Cameras
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A New Way to Factorize Linear Cameras.
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Affine multi-view modelling for close range object measurement
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Reconstruction 3D de l'environnement dynamique d'un véhicule à l'aide d'un système multi-caméras hétérogène en stéréo wide-baseline
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Internal Constraints of the Trifocal Tensor
TL;DR: A second set of minimal and sucient constraints that is simpler is derived and it is shown how this can be used in a new parameterization of the trifocal tensor, which has become an integral part of many projective reconstruction algorithms.