Dense Image Correspondences for Computer Vision

Author:   Tal Hassner ,  Ce Liu
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
ISBN:  

9783319230474


Pages:   295
Publication Date:   02 December 2015
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Dense Image Correspondences for Computer Vision


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Author:   Tal Hassner ,  Ce Liu
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 1.90cm , Length: 23.50cm
Weight:   5.856kg
ISBN:  

9783319230474


ISBN 10:   3319230476
Pages:   295
Publication Date:   02 December 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction 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.

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Author Information

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.

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