6 accepted papers
This paper presents a formation control approach for contactless gesture-based Human-Swarm Interaction (HSI) between a team of multi-rotor Unmanned Aerial Vehicles (UAVs) and a human worker. The approach is designed to monitor the safety of human workers, particularly those operating at heights. In
Industrial pipeline inspection in petrochemical refineries is dangerous, expensive, time-consuming and prone to errors. Anomaly detection can play a crucial role towards its automation. Damages in this type of infrastructure are few and can be considered as anomalies (essentially outliers). This pap…
This paper presents a unified system tailored for autonomous pipe segmentation within an industrial setting. To this end, it is designed to analyze RGB images captured by Unmanned Aerial Vehicle (UAV)-mounted cameras to predict binary pipe segmentation maps. The overall proposed system consists of t…
This paper presents a novel neural module for enhancing existing fast and lightweight 2D human pose estimation CNNs, in order to increase their accuracy. A baseline stem CNN is augmented by a collateral module, which is tasked to encode global spatial and semantic information and provide it to the s…
Camera-equipped UAVs, or drones, are increasingly employed in a wide range of applications. Thus, ensuring their safe flight in areas containing people is a top priority. In this paper, a deep neural network-based method is proposed for the task of visual human crowd detection from UAV footage, allo…