Large-Scale Visual Geo-Localization
Editors: Zamir, A.R., Hakeem, A., Van Gool, L., Shah, M., Szeliski, R. (Eds.)
Free Preview- 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
Buy this book
- 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
Pages 1-18
-
Discovering Mid-level Visual Connections in Space and Time
Pages 21-40
-
Where the Photos Were Taken: Location Prediction by Learning from Flickr Photos
Pages 41-58
-
Cross-View Image Geo-localization
Pages 59-76
-
Ultrawide Baseline Facade Matching for Geo-localization
Pages 77-98
-
Table of contents (17 chapters)
- Download Preface 1 PDF (53.6 KB)
- Download Sample pages 2 PDF (1.5 MB)
- Download Table of contents PDF (67.3 KB)
Recommended for you
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
- Softcover ISBN
- 978-3-319-79840-0
- Series ISSN
- 2191-6586
- Edition Number
- 1
- Number of Pages
- XI, 351
- Number of Illustrations
- 145 b/w illustrations, 7 illustrations in colour
- Topics
