| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Padua, I-35122 Padua - Italy
[2] Univ Estadual Campinas, BR-13083970 Campinas, SP - Brazil
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | IEEE SIGNAL PROCESSING LETTERS; v. 27, p. 1490-1494, 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
The capability of associating an image to its geographical location is a significant concern in journalism and digital forensics. Given the availability of geo-tagged satellite imagery for most of the Earth's surface, retrieving the location of a generic picture can be addressed as a cross-view image matching between aerial and ground views. In this paper, we outline some initial steps toward the development of a fully-unsupervised algorithm for ground-to-aerial image matching, exploiting the view-invariant adjacency relationships of the landmarks appearing in both views. We introduce a graph-based strategy that, given a set of pre-extracted landmarks, localizes the viewpoint of a ground-level 360-degree image within a broad aerial view of the same area, by matching the respective landmark graphs according to a specifically designed likelihood model. (AU) | |
| FAPESP's process: | 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Projects - Thematic Grants |