Advances in Computer Vision and Pattern Recognition

Large-Scale Visual Geo-Localization

Editors: Zamir, A.R., Hakeem, A., Van Gool, L., Shah, M., Szeliski, R. (Eds.)

  • Presents in-depth insights from academic and industry leaders in the field
  • Describes analyses on real-world datasets from the military, government and academia
  • Provides the first extensive review of this emerging field, including discussion of state-of-the-art and potential future developments
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eBook $109.00
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  • ISBN 978-3-319-25781-5
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  • Immediate eBook download after purchase
Hardcover $139.00
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  • ISBN 978-3-319-25779-2
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About this book

This timely and authoritative volume explores the bidirectional relationship between images and locations. The text presents a comprehensive review of the state of the art in large-scale visual geo-localization, and discusses the emerging trends in this area. Valuable insights are supplied by a pre-eminent selection of experts in the field, into a varied range of real-world applications of geo-localization. Topics and features: discusses the latest methods to exploit internet-scale image databases for devising geographically rich features and geo-localizing query images at different scales; investigates geo-localization techniques that are built upon high-level and semantic cues; describes methods that perform precise localization by geometrically aligning the query image against a 3D model; reviews techniques that accomplish image understanding assisted by the geo-location, as well as several approaches for geo-localization under practical, real-world settings.

About the authors

Dr. Amir R. Zamir is a postdoctoral researcher at the Computer Science Department of Stanford University, CA, USA.

Dr. Asaad Hakeem is a Principal Research Scientist in the Machine Learning Division at Decisive Analytics Corporation, Arlington, VA, USA.

Dr. Luc Van Gool is a Full Professor and Head of the Computer Vision Lab at ETH Zurich, Switzerland, and the VISICS Computer Vision at KU Leuven, Belgium. His other publications include the Springer title Detection and Identification of Rare Audio-visual Cues.

Dr. Mubarak Shah is Agere Chair Professor and Director of the Center for Research in Computer Vision at the University of Central Florida, Orlando, FL, USA. He is the Series Editor of Springer’s International Series in Video Computing, and he served as an Editor-in-Chief of the Springer journal Machine Vision and Applications from 2004 to 2015.

Dr. Richard Szeliski is the Director and a founding member of the Computational Photography applied research group at Facebook, Seattle, WA, USA. He is also the author of the best-selling Springer textbook Computer Vision – Algorithms and Applications.

Table of contents (17 chapters)

  • Introduction to Large-Scale Visual Geo-localization

    Zamir, Amir R. (et al.)

    Pages 1-18

  • Discovering Mid-level Visual Connections in Space and Time

    Lee, Yong Jae (et al.)

    Pages 21-40

  • Where the Photos Were Taken: Location Prediction by Learning from Flickr Photos

    Li, Li-Jia (et al.)

    Pages 41-58

  • Cross-View Image Geo-localization

    Lin, Tsung-Yi (et al.)

    Pages 59-76

  • Ultrawide Baseline Facade Matching for Geo-localization

    Bansal, Mayank (et al.)

    Pages 77-98

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-25781-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.00
price for USA
  • ISBN 978-3-319-25779-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Large-Scale Visual Geo-Localization
Editors
  • Amir R. Zamir
  • Asaad Hakeem
  • Luc Van Gool
  • Mubarak Shah
  • Richard Szeliski
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-25781-5
DOI
10.1007/978-3-319-25781-5
Hardcover ISBN
978-3-319-25779-2
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XI, 351
Number of Illustrations and Tables
145 b/w illustrations, 7 illustrations in colour
Topics