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OverviewThis 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. Full Product DetailsAuthor: Tal Hassner , Ce LiuPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: Softcover reprint of the original 1st ed. 2016 Weight: 4.686kg ISBN: 9783319359144ISBN 10: 3319359142 Pages: 295 Publication Date: 23 August 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction to Dense Optical Flow.- SIFT Flow: Dense Correspondence across Scenes and its Applications.- Dense, Scale-Less Descriptors.- Scale-Space SIFT Flow.- Dense Segmentation-aware Descriptors.- SIFTpack: A Compact Representation for Efficient SIFT Matching.- In Defense of Gradient-Based Alignment on Densely Sampled Sparse Features.- From Images to Depths and Back.- DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling.- Joint Inference in Image Datasets via Dense Correspondence.- Dense Correspondences and Ancient Texts.ReviewsAuthor InformationProf. 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. Tab Content 6Author Website:Countries AvailableAll regions |
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