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International Journal of Computer Vision

Erschienen in:

18.11.2023

Image and Object Geo-Localization

verfasst von: Daniel Wilson, Xiaohan Zhang, Waqas Sultani, Safwan Wshah

Erschienen in: International Journal of Computer Vision | Ausgabe 4/2024

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Abstract

The concept of geo-localization broadly refers to the process of determining an entity’s geographical location, typically in the form of Global Positioning System (GPS) coordinates. The entity of interest may be an image, a sequence of images, a video, a satellite image, or even objects visible within the image. Recently, massive datasets of GPS-tagged media have become available due to smartphones and the internet, and deep learning has risen to prominence and enhanced the performance capabilities of machine learning models. These developments have enabled the rise of image and object geo-localization, which has impacted a wide range of applications such as augmented reality, robotics, self-driving vehicles, road maintenance, and 3D reconstruction. This paper provides a comprehensive survey of visual geo-localization, which may involve either determining the location at which an image has been captured (image geo-localization) or geolocating objects within an image (object geo-localization). We will provide an in-depth study of visual geo-localization including a summary of popular algorithms, a description of proposed datasets, and an analysis of performance results to illustrate the current state of the field.

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Titel: Image and Object Geo-Localization
verfasst von: Daniel Wilson
Xiaohan Zhang
Waqas Sultani
Safwan Wshah
Publikationsdatum: 18.11.2023
Verlag: Springer US
Erschienen in: International Journal of Computer Vision / Ausgabe 4/2024
Print ISSN: 0920-5691
Elektronische ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-023-01942-3

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