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A survey on moving object detection for wide area motion imagery

: Sommer, L.; Teutsch, Michael; Schuchert, Tobias; Beyerer, Jürgen

Postprint urn:nbn:de:0011-n-4324643 (7.9 MByte PDF)
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Created on: 7.2.2017

Institute of Electrical and Electronics Engineers -IEEE-:
WACV 2016, IEEE Winter Applications of Computer Vision Workshops : March 7-9, 2016 in Lake Placid, New York, USA
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-2115-4 (Print)
ISBN: 978-1-5090-2114-7 (Online)
ISBN: 978-1-5090-0642-7
Winter Conference on Applications of Computer Vision (WACV) <2016, Lake Placid/NY>
Workshop on Computer Vision Applications in Surveillance and Transportation <1, 2016, Lake Placid/NY>
Workshop on Automated Analysis of Video Data for Wildlife Surveillance <2, 2016, Lake Placid/NY>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Wide Area Motion Imagery (WAMI) enables the surveillance of tens of square kilometers with one airborne sensor. Each image can contain thousands of moving objects. Applications such as driver behavior analysis or traffic monitoring require precise multiple object tracking that is dependent on initial detections. However, low object resolution, dense traffic, and imprecise image alignment lead to split, merged, and missing detections. No systematic evaluation of moving object detection exists so far although many approaches have been presented in the literature. This paper provides a detailed overview of existing methods for moving object detection in WAMI data. Also we propose a novel combination of short-term background subtraction and suppression of image alignment errors by pixel neighborhood consideration. In total, eleven methods are systematically evaluated using more than 160,000 ground truth detections of the WPAFB 2009 dataset. Best performance with respect to precision and recall is achieved by the proposed one.