Drone-vs-Bird detection challenge at IEEE AVSS2017

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Date

2017-09-01

Author

Coluccia, Angelo
Ghenescu, Marian
Piatrik, Tomas
De Cubber, Geert
Schumann, Arne
Sommer, Lars
Klatte, Johannes
Schuchert, Tobias
Beyerer, Juergen
Farhadi, Mohammad
Amandi, Ruhallah
Aker, Cemal
Kalkan, Sinan
Saqib, Muhammad
Sharma, Nabin
Makkah, Sultan Daud Khan
Blumenstein, Michael

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Drones, Birds, Measurement, Surveillance, Video sequences, Lighting, Convolution

URI

https://hdl.handle.net/11511/36297

DOI

https://doi.org/10.1109/avss.2017.8078464

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

A. Coluccia et al., “Drone-vs-Bird detection challenge at IEEE AVSS2017,” 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36297.