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Drone-vs-Bird detection challenge at IEEE AVSS2017

: Coluccia, A.; Ghenescu, M.; Piatrik, T.; Cubber, G. de; Schumann, A.; Sommer, L.; Klatte, J.; Schuchert, Tobias; Beyerer, Jürgen; Farhadi, M.; Amandi, R.; Aker, C.; Kalkan, S.; Saqib, M.; Sharma, N.; Daud, S.; Makkah, K.; Blumenstein, M.

Fulltext urn:nbn:de:0011-n-4819047 (2.9 MByte PDF)
MD5 Fingerprint: 69eb42f8572944b7576bfdff5fed3aae
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Created on: 8.2.2018

Institute of Electrical and Electronics Engineers -IEEE-:
14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 : August 29, 2017-September 1, 2017, Lecce
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-2939-0
ISBN: 978-1-5386-2940-6 (Print)
International Conference on Advanced Video and Signal Based Surveillance (AVSS) <14, 2017, Lecce>
European Commission EC
H2020; 700643; SafeShore
System for detection of Threat Agents in Maritime Border Environment
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
bird detection; illegal activity; position estimates

Small drones are a rising threat due to their possible misuse for illegal activities, in particular smuggling and terrorism. The project SafeShore, funded by the European Commission under the Horizon 2020 program, has launched the 'drone-vs-bird detection challenge' to address one of the many technical issues arising in this context. The goal is to detect a drone appearing at some point in a video where birds may be also present: the algorithm should raise an alarm and provide a position estimate only when a drone is present, while not issuing alarms on birds. This paper reports on the challenge proposal, evaluation, and results.