Drone-vs-Bird detection challenge at IEEE AVSS2017

Coluccia, A; Ghenescu, M; Piatrik, T; De Cubber, G; Schumann, A; Sommer, L; Klatte, J; Schuchert, T; Beyerer, J; Farhadi, M; Amandi, R; Aker, C; Kalkan, S; Saqib, M; Sharma, N; Makkah, SDK; Blumenstein, M

Drone-vs-Bird detection challenge at IEEE AVSS2017

Coluccia, A Ghenescu, M Piatrik, T De Cubber, G Schumann, A Sommer, L Klatte, J Schuchert, T Beyerer, J Farhadi, M Amandi, R Aker, C Kalkan, S Saqib, M

Sharma, N

Makkah, SDK Blumenstein, M

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Publication Type:: Conference Proceeding
Citation:: 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017, 2017
Issue Date:: 2017-10-20

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Field	Value	Language
dc.contributor.author	Coluccia, A	en_US
dc.contributor.author	Ghenescu, M	en_US
dc.contributor.author	Piatrik, T	en_US
dc.contributor.author	De Cubber, G	en_US
dc.contributor.author	Schumann, A	en_US
dc.contributor.author	Sommer, L	en_US
dc.contributor.author	Klatte, J	en_US
dc.contributor.author	Schuchert, T	en_US
dc.contributor.author	Beyerer, J	en_US
dc.contributor.author	Farhadi, M	en_US
dc.contributor.author	Amandi, R	en_US
dc.contributor.author	Aker, C	en_US
dc.contributor.author	Kalkan, S	en_US
dc.contributor.author	Saqib, M https://orcid.org/0000-0003-4374-0888	en_US
dc.contributor.author	Sharma, N https://orcid.org/0000-0003-0841-1245	en_US
dc.contributor.author	Makkah, SDK	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.available	2020-05-25T19:18:01Z
dc.date.issued	2017-10-20	en_US
dc.identifier.citation	2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017, 2017	en_US
dc.identifier.isbn	9781538629390	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126337
dc.description.abstract	© 2017 IEEE. 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 results1.	en_US
dc.relation.ispartof	2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017	en_US
dc.relation.isbasedon	10.1109/AVSS.2017.8078464	en_US
dc.title	Drone-vs-Bird detection challenge at IEEE AVSS2017	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. 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 results1.

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http://hdl.handle.net/10453/126337