Mattyus, Gellert Sandor und Fraundorfer, Friedrich (2016) Aerial image sequence geolocalization with road traffic as invariant feature. Image and Vision Computing, 52 (8), Seiten 218-229. Elsevier. doi: 10.1016/j.imavis.2016.05.014. ISSN 0262-8856.
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Offizielle URL: http://www.sciencedirect.com/science/article/pii/S0262885616301056
Kurzfassung
The geolocalization of aerial images is important for extracting geospatial information (e.g. the position of buildings, streets, cars, etc.) and for creating maps. The standard is to use an expensive aerial imaging system equipped with an accurate GPS and IMU and/or do laborious Ground Control Point measurements. In this paper we present a novel method to recognize the geolocation of aerial images automatically without any GPS or (Inertial Measurement Unit) IMU. We extract road segments in the image sequence by detecting and tracking cars. We search in a database created from a road network map for the best matches between the road database and the extracted road segments. Geometric hashing is used to retrieve a shortlist of matches. The matches in the shortlist are ranked by a verification process. The highest scoring match gives the location and orientation of the images. We show in the experiments that our method can correctly geolocalize the aerial images in various scenes: e.g. urban, suburban, rural with motorway. Beside the current images only the road map is needed over the search area. We can search an area of 22500 km2 containing 32000 km of streets within minutes on a single cpu.
elib-URL des Eintrags: | https://elib.dlr.de/104671/ | ||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||
Titel: | Aerial image sequence geolocalization with road traffic as invariant feature | ||||||||||||
Autoren: |
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Datum: | 20 Juni 2016 | ||||||||||||
Erschienen in: | Image and Vision Computing | ||||||||||||
Referierte Publikation: | Ja | ||||||||||||
Open Access: | Ja | ||||||||||||
Gold Open Access: | Nein | ||||||||||||
In SCOPUS: | Ja | ||||||||||||
In ISI Web of Science: | Ja | ||||||||||||
Band: | 52 | ||||||||||||
DOI: | 10.1016/j.imavis.2016.05.014 | ||||||||||||
Seitenbereich: | Seiten 218-229 | ||||||||||||
Herausgeber: |
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Verlag: | Elsevier | ||||||||||||
ISSN: | 0262-8856 | ||||||||||||
Status: | veröffentlicht | ||||||||||||
Stichwörter: | Image Processing, Computer Vision, Aerial images, Remote Sensing, Geolocalization, Georeferencing, Geotagging, Geometric Hashing | ||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||
HGF - Programm: | Verkehr | ||||||||||||
HGF - Programmthema: | Verkehrsmanagement (alt) | ||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||
DLR - Forschungsgebiet: | V VM - Verkehrsmanagement | ||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - Vabene++ (alt) | ||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Photogrammetrie und Bildanalyse | ||||||||||||
Hinterlegt von: | Mattyus, Gellert Sandor | ||||||||||||
Hinterlegt am: | 20 Jun 2016 15:34 | ||||||||||||
Letzte Änderung: | 08 Nov 2023 15:22 |
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