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Drone-vs-Bird Detection Challenge at IEEE AVSS2021

Angelo Coluccia, Alessio Fascista, Arne Schumann, Lars Sommer, Anastasios Dimou, Dimitrios Zarpalas, Fatih Çağatay Akyön, Ogulcan Eryuksel, Kamil Anil Ozfuttu, Sinan Onur Altinuc, Fardad Dadboud, Vaibhav Patel, Varun Mehta, Miodrag Bolić, Iraj Mantegh

202172 citationsDOI

Abstract

This paper presents the 4-th edition of the “drone-vs-bird” detection challenge, launched in conjunction with the the 17-th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS). The objective of the challenge is to tackle the problem of detecting the presence of one or more drones in video scenes where birds may suddenly appear, taking into account some important effects such as the background and foreground motion. The proposed solutions should identify and localize drones in the scene only when they are actually present, without being confused by the presence of birds and the dynamic nature of the captured scenes. The paper illustrates the results of the challenge on the 2021 dataset, which has been further extended compared to the previous edition run in 2020.

Topics & Concepts

DroneComputer scienceComputer securityGeneticsBiologySmart Agriculture and AIAdvanced Neural Network ApplicationsUAV Applications and Optimization