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Proceedings Paper

Video change detection for fixed wing UAVs
Author(s): Jan Bartelsen; Thomas Müller; Jochen Ring; Klaus Mück; Stefan Brüstle; Bastian Erdnüß; Bastian Lutz; Theresa Herbst
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Paper Abstract

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the image processing and change detection, we use the approach of Muller.4 Although it was developed for unmanned ground vehicles (UGVs), it enables a near real time video change detection for aerial videos. Concluding, we discuss the demands on sensor systems in the matter of change detection.

Paper Details

Date Published: 5 October 2017
PDF: 13 pages
Proc. SPIE 10432, Target and Background Signatures III, 104320K (5 October 2017); doi: 10.1117/12.2278094
Show Author Affiliations
Jan Bartelsen, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Thomas Müller, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Jochen Ring, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Klaus Mück, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Stefan Brüstle, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Bastian Erdnüß, Karlsruhe Institute of Technology (Germany)
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Bastian Lutz, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Theresa Herbst, Univ. Heidelberg (Germany)
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)


Published in SPIE Proceedings Vol. 10432:
Target and Background Signatures III
Karin U. Stein; Ric Schleijpen, Editor(s)

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