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Drone-vs-Bird Detection Challenge at IEEE AVSS2019

Authors: Angelo Coluccia; Muhammad Saqib; Nabin Sharma; Michael Blumenstein; Vasileios Magoulianitis; Dimitrios Ataloglou; Anastasios Dimou; +16 Authors

Drone-vs-Bird Detection Challenge at IEEE AVSS2019

Abstract

This paper presents the second edition of the “drone-vs-bird” detection challenge, launched within the activities of the 16-th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS). The challenge's goal is to detect one or more drones appearing at some point in video sequences where birds may be also present, together with motion in background or foreground. Submitted algorithms should raise an alarm and provide a position estimate only when a drone is present, while not issuing alarms on birds, nor being confused by the rest of the scene. This paper reports on the challenge results on the 2019 dataset, which extends the first edition dataset provided by the SafeShore project with additional footage under different conditions.

Countries
Italy, Germany
Keywords

ddc:004, DATA processing & computer science, info:eu-repo/classification/ddc/004, 004

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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