Presentation + Paper
4 May 2017 Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras
Author Affiliations +
Abstract
Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Müller "Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras", Proc. SPIE 10190, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII, 1019018 (4 May 2017); https://doi.org/10.1117/12.2262575
Lens.org Logo
CITATIONS
Cited by 23 scholarly publications and 3 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Unmanned aerial vehicles

Cameras

Short wave infrared radiation

Detection and tracking algorithms

Sensors

Image processing

Long wavelength infrared

RELATED CONTENT

Towards a real-time wide area motion imagery system
Proceedings of SPIE (October 21 2015)
Efficient object tracking in WAAS data streams
Proceedings of SPIE (February 02 2011)
Real-time enhanced vision system
Proceedings of SPIE (May 25 2005)
Mosaics from video with burned-in metadata
Proceedings of SPIE (May 10 2005)

Back to Top