Aerial vehicles detection and recognition for UAV vision system

Abstract

This article focuses on aerial vehicle detection and recognition by a wide field of view monocular vision system that can be installed on UAVs (unmanned aerial vehicles). The objects are mostly observed on the background of clouds under regular daylight conditions. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The described algorithm is able to detect small targets, but unlike many other approaches is designed to work with large-scale objects as well. The suggested algorithm is also intended to recognize and track the aerial vehicles of specific kind using a set of reference objects defined by their 3D models. For that purpose a computationally efficient contour descriptor for the models and the test objects is calculated. An experimental research on real video sequences is performed. The video database contains different types of aerial vehicles: airplanes, helicopters, and UAVs. The proposed approach shows good accuracy in all case studies and can be implemented in onboard vision systems.