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Sinopsis
This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.
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Acerca del autor
Prof. Tal Hassner is a faculty member of the Department of Mathematics and Computer Science, The Open University of Israel, Israel. Ce Liu is a Researcher with Google.
De la contraportada
This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code, and data necessary for expediting the development of effective correspondence-based computer vision systems.
· Provides in-depth coverage of dense-correspondence estimation
· Covers both the breadth and depth of new achievements in dense correspondence estimation and their applications
· Includes information for designing computer vision systems that rely on efficient and robust correspondence estimation
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Dense Image Correspondences for Computer Vision
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Springer International Publishing, 2016
ISBN 10: 3319359142
ISBN 13: 9783319359144
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides in-depth coverage of dense-correspondence estimationCovers both the breadth and depth of new achievements in dense correspondence estimation and their applicationsIncludes information for designing computer vision systems which rel. Nº de ref. del artículo: 448747122
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Dense Image Correspondences for Computer Vision
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Dense Image Correspondences for Computer Vision
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Springer International Publishing Aug 2016, 2016
ISBN 10: 3319359142
ISBN 13: 9783319359144
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems. 308 pp. Englisch. Nº de ref. del artículo: 9783319359144
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Dense Image Correspondences for Computer Vision
Publicado por
Springer International Publishing, Springer International Publishing, 2016
ISBN 10: 3319359142
ISBN 13: 9783319359144
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