Unmanned aerial vehicles (UAVs), most commonly known as drones, are increasingly used as a technological support tool for search-and-rescue (SAR) operations (and post-disaster area explorations as well). UAVs equipped with high-resolution cameras and embedded, yet powerful GPUs, in fact, can provide an effective and efficient aid to emergency rescue operations, mainly because locating victims, which may be unconscious or injured, as much fast as possible, is crucial to improve their chance of survival. In particular, the use of drones that are able to automatically detect people in the scenes can increase detection rate, while reducing rescue time. In this repository, we provide a new dataset specifically conceived for SAR operations from drones with computer vision. As it is small-sized, the dataset is currently intended for testing and evaluation purposes only. The main aim of the repository is to encourage contributions on this intriguing topic. In particular, any contribution to make the dataset bigger is welcome.

Search-and-Rescue From Drones With Computer Vision

Giovanna Castellano;Gennaro Vessio
2020-01-01

Abstract

Unmanned aerial vehicles (UAVs), most commonly known as drones, are increasingly used as a technological support tool for search-and-rescue (SAR) operations (and post-disaster area explorations as well). UAVs equipped with high-resolution cameras and embedded, yet powerful GPUs, in fact, can provide an effective and efficient aid to emergency rescue operations, mainly because locating victims, which may be unconscious or injured, as much fast as possible, is crucial to improve their chance of survival. In particular, the use of drones that are able to automatically detect people in the scenes can increase detection rate, while reducing rescue time. In this repository, we provide a new dataset specifically conceived for SAR operations from drones with computer vision. As it is small-sized, the dataset is currently intended for testing and evaluation purposes only. The main aim of the repository is to encourage contributions on this intriguing topic. In particular, any contribution to make the dataset bigger is welcome.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/312221
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