Multi-Resolution Face Recognition with Drones

Smart cameras have recently seen a large diffusion and represent a low-cost solution for improving public security in many scenarios. Moreover, they are light enough to be lifted by a drone. Face recognition enabled by drones equipped with smart cameras has already been reported in the literature. However, the use of the drone generally imposes tighter constraints than other facial recognition scenarios. First, weather conditions, such as the presence of wind, pose a severe limit on image stability. Moreover, the distance the drones fly is typically much high than fixed ground cameras, which inevitably translates into a degraded resolution of the face images. Furthermore, the drones' operational altitudes usually require the use of optical zoom, thus amplifying the harmful effects of their movements. For all these reasons, in drone scenarios, image degradation strongly affects the behavior of face detection and recognition systems. In this work, we studied the performance of deep neural networks for face re-identification specifically designed for low-quality images and applied them to a drone scenario using a publicly available dataset known as DroneSURF.