Víctor García Rubio

Associated with Visiona Ingeniería de ProyectosAssociated with Visiona Ingeniería de Proyectos Published on MDPI Sensors Journal. Part of and predictive mainteinance solutions in the scope of NRG-5 EU project. Deep Learning and Computer vision project to prevent accidents on critical infraestructures by detecting changes on security flights performed by drones. In recent years, the use of unmanned aerial vehicles (UAVs) for surveillance tasks has increased considerably. This technology provides a versatile and innovative approach to the field. However, the automation of tasks such as object recognition or change detection usually requires image processing techniques. In this paper we present a system for change detection in video sequences acquired by moving cameras. It is based on the combination of image alignment techniques with a deep learning model based on convolutional neural networks (CNNs). This approach covers two important topics. Firstly, the capability of our system to be adaptable to variations in the UAV flight. In particular, the difference of height between flights, and a slight modification of the camera’s position or movement of the UAV because of natural conditions such as the effect of wind. Secondly, the precision of our model to detect changes in diverse environments, which has been compared with state-of-the-art methods in change detection.