Autor(es)

Verde, Sebastiano ^[1] ; Resek, Thiago ^[2] ; Milani, Simone ^[1] ; Rocha, Anderson ^[2]

Afiliação do(s) autor(es)

^[1] Univ Padua, I-35122 Padua - Italy

^[2] Univ Estadual Campinas, BR-13083970 Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IEEE SIGNAL PROCESSING LETTERS; v. 27, p. 1490-1494, 2020.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 17/12646-3 - Déjà vu: coerência temporal, espacial e de caracterização de dados heterogêneos para análise e interpretação de integridade
• Beneficiário: Anderson de Rezende Rocha
• Modalidade de apoio: Auxílio à Pesquisa - Temático