Visual real-time detection, recognition and tracking of ground and airborne targets

Abstract

This paper presents methods and algorithms for real-time visual target detection, recognition and tracking, both in the case of ground-based objects (surveyed from a moving airborne imaging sensor) and flying targets (observed from a groundbased or vehicle mounted sensor). The methods are highly parallelized and partially implemented on GPU, with the goal of real-time speeds even in the case of multiple target observations. Real-time applicability is in focus. The methods use single camera observations, providing a passive and expendable alternative for expensive and/or active sensors. Use cases involve perimeter defense and surveillance situations, where passive detection and observation is a priority (e.g. aerial surveillance of a compound, detection of reconnaissance drones, etc.).

Aerial vehicles detection and recognition for UAV vision system

“…The algorithm provides detection probability of more than 90 % with a false negative ratio not exceeding 5 %, but the algorithm is not developed for large-sized object detection. A closer analogue of the developed algorithm is a multistep approach described in [15], which provides detection and classification of aerial objects. The algorithm demonstrated high detection quality; however, test video sequences contained only aircraft on relatively low contrast background.…”

“…However, some relatively recent research efforts look promising [4,5]. The alternative approaches based on algorithm switching already applied for ground object detection, for example [6].…”