Dense Image Correspondences for Computer Vision - Image 1

£64.87

Springer Dense Image Correspondences for Computer Vision

Name: Geox Women's D New ERAKLIA 15 D Slide Sandal, Papyrus, 4 UK
Brand: Springer
Price: 64.91 GBP
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Product Description 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. From the Back Cover 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 About the Author 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.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 3319359142
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 23 August 2016
Listed Since: 19 May 2016

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Springer Dense Image Correspondences for Computer Vision

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