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A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles

1
Interdisciplinary Center for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg, Luxembourg
2
Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, 73100 Lecce, Italy
*
Author to whom correspondence should be addressed.
J. Imaging 2020, 6(8), 78; https://doi.org/10.3390/jimaging6080078
Received: 29 June 2020 / Revised: 27 July 2020 / Accepted: 31 July 2020 / Published: 4 August 2020
The spread of Unmanned Aerial Vehicles (UAVs) in the last decade revolutionized many applications fields. Most investigated research topics focus on increasing autonomy during operational campaigns, environmental monitoring, surveillance, maps, and labeling. To achieve such complex goals, a high-level module is exploited to build semantic knowledge leveraging the outputs of the low-level module that takes data acquired from multiple sensors and extracts information concerning what is sensed. All in all, the detection of the objects is undoubtedly the most important low-level task, and the most employed sensors to accomplish it are by far RGB cameras due to costs, dimensions, and the wide literature on RGB-based object detection. This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation of such solutions for operations of the UAV. Moreover, a new taxonomy that considers different heights intervals and driven by the methodological approaches introduced by the works in the state of the art instead of hardware, physical and/or technological constraints is proposed. View Full-Text
Keywords: computer vision; 2d object detection; unmanned aerial vehicles; deep learning computer vision; 2d object detection; unmanned aerial vehicles; deep learning
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MDPI and ACS Style

Cazzato, D.; Cimarelli, C.; Sanchez-Lopez, J.L.; Voos, H.; Leo, M. A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles. J. Imaging 2020, 6, 78. https://doi.org/10.3390/jimaging6080078

AMA Style

Cazzato D, Cimarelli C, Sanchez-Lopez JL, Voos H, Leo M. A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles. Journal of Imaging. 2020; 6(8):78. https://doi.org/10.3390/jimaging6080078

Chicago/Turabian Style

Cazzato, Dario; Cimarelli, Claudio; Sanchez-Lopez, Jose L.; Voos, Holger; Leo, Marco. 2020. "A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles" J. Imaging 6, no. 8: 78. https://doi.org/10.3390/jimaging6080078

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