Large-Scale Visual Geo-Localization / Advances in Computer Vision and Pattern Recognition (PDF)
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...
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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 - Presents contributions from the leading and most active
researchers in the field from both academia and industry
This invaluable text/reference is a must-read for all
researchers interested in developing automatic methods for image
geo-localization, whether for commercial, academic, or military domains.
Professionals involved in computer vision, computer graphics, photogrammetry,
computational optimization, geographic information systems, and other related
disciplines, will also benefit from the detailed coverage of this emerging
field.
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.
- 2016, 1st ed. 2016, 351 Seiten, Englisch
- Herausgegeben: Amir R. Zamir, Asaad Hakeem, Luc van Gool, Mubarak Shah, Richard Szeliski
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319257811
- ISBN-13: 9783319257815
- Erscheinungsdatum: 05.07.2016
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 18 MB
- Ohne Kopierschutz
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