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Automatic geo‐localization framework without GNSS data.

Authors :
Tang, Jin
Gong, Cheng
Guo, Fan
Yang, Zirong
Wu, Zhihu
Source :
IET Image Processing (Wiley-Blackwell); Jun2022, Vol. 16 Issue 8, p2180-2195, 16p
Publication Year :
2022

Abstract

The information unavailability of a global navigation satellite system (GNSS) for geo‐localization in many military and tourism applications implies the need to employ other applicable types of information, such as automatic image‐based location recognition. Unlike most existing localization methods that use GNSS information to locate an initial position, this paper proposes an automatic geo‐localization framework that does not require GNSS data. The proposed framework is a two‐stage pipeline that uses a query image and digital elevation model (DEM) data as input. The authors frame automatic geo‐localization without GNSS recordings as a skyline matching problem. By extracting the skyline from the DEM data and query images, the query image can be localized by matching the query skyline feature to the DEM skyline database. It has been demonstrated that this low‐cost approach can perform efficiently in mountainous or hilly areas to produce reliable localization results. The system was tested on 50 testing site points within a large‐scale area (China, 202.6 km2), and an average position error of 43.13 m was detected within 4.5 s. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17519659
Volume :
16
Issue :
8
Database :
Complementary Index
Journal :
IET Image Processing (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
156901635
Full Text :
https://doi.org/10.1049/ipr2.12482