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An Operational System for Estimating Road Traffic Information from Aerial Images

Leitloff, J.; Rosenbaum, D.; Kurz, F.; Meynberg, O.; Reinartz, P.


Given that ground stationary infrastructures for traffic monitoring are barely able to handle everyday traffic volumes, there is a risk that they could fail altogether in situations arising from mass events or disasters. In this work, we present an alternative approach for traffic monitoring during disaster and mass events, which is based on an airborne optical sensor system. With this system, optical image sequences are automatically examined on board an aircraft to estimate road traffic information, such as vehicle positions, velocities and driving directions. The traffic information, estimated in real time on board, is immediately downlinked to a ground station. The airborne sensor system consists of a three-head camera system, a real-time-capable GPS/INS unit, five industrial PCs and a downlink unit. The processing chain for automatic extraction of traffic information contains modules for the synchronization of image and navigation data streams, orthorectification and vehicle detection and tracking modules. The vehicle detector is based on a combination of AdaBoost and support vector machine classifiers. Vehicle tracking relies on shape-based matching operators. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000087449
Veröffentlicht am 15.11.2018
DOI: 10.3390/rs61111315
Zitationen: 84
Web of Science
Zitationen: 71
Zitationen: 73
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2014
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000087449
Erschienen in Remote sensing
Verlag MDPI
Band 6
Heft 11
Seiten 11315–11341
Schlagwörter monitoring; pattern recognition; orthorectification; georeferencing; sequences; tracking; vehicle detection
Nachgewiesen in Web of Science
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