Automatic geo‐localization framework without GNSS data. Issue 8 (30th March 2022)

• Record Type: Journal Article
• Authors: Tang, Jin; Gong, Cheng; Guo, Fan; Yang, Zirong; Wu, Zhihu
• Is Part Of: IET image processing. Volume 16:Issue 8(2022)
• Page Start: 2180
• Page End: 2195
• Publication Date: 2022-03-30
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12482
• Languages: English
• ISSNs: 1751-9659

Abstract

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 km 2 ), and an average position error of 43.13 m was detected within 4.5 s.