Large-Scale Visual Geo-Localization

Dr. Amir R. Zamir is a postdoctoral researcher at theComputer Science Department of Stanford University, CA, USA.Dr. Asaad Hakeem is a Principal Research Scientist in theMachine Learning Division at Decisive Analytics Corporation, Arlington, VA,USA.Dr. Luc Van Gool is a Full Professor and Head of theComputer Vision Lab at ETH Zurich, Switzerland, and the VISICS Computer Vision atKU Leuven, Belgium. His other publications include the Springer title Detectionand Identification of Rare Audio-visual Cues.Dr. Mubarak Shah is Agere Chair Professor and Director ofthe Center for Research in Computer Vision at the University of CentralFlorida, Orlando, FL, USA. He is the Series Editor of Springer’s InternationalSeries in Video Computing, and he served as an Editor-in-Chief of the Springerjournal Machine Vision and Applications from 2004 to 2015.Dr. Richard Szeliski is the Director and a founding memberof the Computational Photography applied research group at Facebook, Seattle,WA, USA. He is also the author of the best-selling Springer textbook ComputerVision – Algorithms and Applications.

• Introduction to Large Scale Visual Geo-Localization.- Part I: Data-Driven Geo-Localization.- Discovering Mid-Level Visual Connections in Space and Time.- Where the Photos Were Taken: Location Prediction by Learning from Flickr Photos.- Cross-View Image Geo-Localization.- Ultra-Wide Baseline Facade Matching for Geo-Localization.- Part II: Semantic Reasoning-Based Geo-Localization.- Semantically Guided Geo-Localization and Modeling in Urban Environments.- Recognizing Landmarks in Large-Scale Social Image Collections.- Part III: Geometric Matching-Based Geo-Localization.- Worldwide Pose Estimation Using 3D Point Clouds.- Exploiting Spatial and Co-Visibility Relations for Image-Based Localization.- 3D Point Cloud Reduction Using Mixed-Integer Quadratic Programming.- Image-Based Large-Scale Geo-Localization in Mountainous Regions.- Adaptive Rendering for Large-Scale Skyline Characterization and Matching.- User-Aided Geo-Localization of Untagged Desert Imagery.- Visual Geo-Localization of Non-Photographic Depictions via 2D-3D Alignment.- Part IV: Real-World Applications.- A Memory Efficient Discriminative Approach for Location-Aided Recognition.- A Real-World System for Image/Video Geo-Localization.- Photo Recall: Using the Internet to Label Your Photos.