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Generating Object Proposals for Vehicle Detection in Aerial Images : Technical Report IES-2016-08

Sommer, Lars


Vehicle detection in aerial images is an important task in many applications such as screening of large areas or traffic monitoring. In general, classifiers or a cascade of classifiers within a sliding window approach
are used to perform vehicle detection. However, sliding window approaches are limited for vehicle detection in a real-time system due to the huge number of windows to classify. To overcome this challenge, several objects
proposals methods have been proposed for generating candidate windows in detection frameworks. Impressive results have been achieved on common detection benchmark datasets like Pascal VOC 2007 for a significantly
reduced number of candidate windows. However, these datasets, which are used to develop the object proposals methods, exhibit considerably differing characteristics compared to aerial images. In this report, we examine
the applicability of such object proposals methods for vehicle detection in aerial images. Therefore, we evaluate the performance of seven state-ofthe-art object proposals methods on the publicly available DLR 3K Munich
Vehicle Aerial Image Dataset. Relevant adaptions are highlighted by using the Selective Search method. ... mehr

Volltext §
DOI: 10.5445/KSP/1000070009
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2017
Sprache Englisch
Identifikator ISBN: 978-3-7315-0678-2
ISSN: 1863-6489
KITopen-ID: 1000072353
Erschienen in Proceedings of the 2016 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision an Fusion Laboratory. Ed.: J. Beyerer
Verlag KIT Scientific Publishing
Seiten 109-122
Serie Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 33
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