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Monitoring for Intrusion Behaviors with a Small UAV
Josiah Yoder,Hyukseong Kwon,Rajnikant Sharma,Daniel Pack 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
In this paper we present behavior recognition algorithms using images captured by a small UAV (unmanned aerial vehicle). Small UAVs provide a mobile platform capable of monitoring a large area, but each UAV has a limited field of view, resulting in very brief observations of targets of interest as UAVs fly over them. Standard behavior recognition algorithms are designed for CCTV networks, where cameras have a fixed view of the target area. To apply these algorithms to imagery from small UAVs, we first geo-locate targets based on their image coordinates and correspondences between geo-located landmarks and landmarks in each video frame. We then apply behavior recognition algorithms that are suited to very short observation periods. We test these algorithms in a simulation environment incorporating realistic target motion and validate the entire approach on imagery captured by a small UAV. These experiments illustrate that automatic behavior recognition has merit even during brief fly-overs, typical of a small UAV on surveillance patrol.
Hyukseong Kwon,Rajnikant Sharma,Josiah Yoder,Daniel Pack 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
Recently, the task of localizing mobile ground targets using airborne images captured by unmanned aerial vehicles (UAVs) has received an increased interest of researchers in the UAV community. The task is even more difficult when position information of a UAV, estimated by Global Positioning System (GPS) signals, becomes unavailable. In this paper, we propose a new method to compute the UAV attitude and thus locate mobile ground targets using ground landmarks obtained from SIFT (Scale-Invariant Feature Transform) features. We show the validity of the proposed method using experimental flight data.