Liu, Kang und Mattyus, Gellert (2015) Fast Multiclass Vehicle Detection on Aerial Images. IEEE Geoscience and Remote Sensing Letters, 12 (9), Seiten 1938-1942. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LGRS.2015.2439517. ISSN 1545-598X.
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Offizielle URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7122912
Kurzfassung
Detecting vehicles in aerial images provides important information for traffic management and urban planning. Detecting the cars in the images is challenging due to the relatively small size of the target objects and the complex background in man-made areas. It is particularly challenging if the goal is near-real-time detection, i.e., within few seconds, on large images without any additional information, e.g., road database and accurate target size. We present a method that can detect the vehicles on a 21-MPixel original frame image without accurate scale information within seconds on a laptop single threaded. In addition to the bounding box of the vehicles, we extract also orientation and type (car/truck) information. First, we apply a fast binary detector using integral channel features in a soft-cascade structure. In the next step, we apply a multiclass classifier on the output of the binary detector, which gives the orientation and type of the vehicles. We evaluate our method on a challenging data set of original aerial images over Munich and a data set captured from an unmanned aerial vehicle (UAV).
elib-URL des Eintrags: | https://elib.dlr.de/96765/ | ||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||
Titel: | Fast Multiclass Vehicle Detection on Aerial Images | ||||||||||||
Autoren: |
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Datum: | September 2015 | ||||||||||||
Erschienen in: | IEEE Geoscience and Remote Sensing Letters | ||||||||||||
Referierte Publikation: | Ja | ||||||||||||
Open Access: | Ja | ||||||||||||
Gold Open Access: | Nein | ||||||||||||
In SCOPUS: | Ja | ||||||||||||
In ISI Web of Science: | Ja | ||||||||||||
Band: | 12 | ||||||||||||
DOI: | 10.1109/LGRS.2015.2439517 | ||||||||||||
Seitenbereich: | Seiten 1938-1942 | ||||||||||||
Herausgeber: |
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Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||
ISSN: | 1545-598X | ||||||||||||
Status: | veröffentlicht | ||||||||||||
Stichwörter: | Detectors;Feature extraction;Histograms;Roads;Training;Vehicle detection;Vehicles;Classification;near real-time;vehicle detection | ||||||||||||
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: | 24 Jun 2015 09:41 | ||||||||||||
Letzte Änderung: | 28 Nov 2023 08:32 |
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