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Vision Based Victim Detection from Unmanned Aerial Vehicles

By Mykhaylo Andriluka, Paul Schnitzspan, Johannes Meyer, Stefan Kohlbrecher, Karen Petersen, Oskar Von Stryk, Stefan Roth and Bernt Schiele


Abstract — Finding injured humans is one of the primary goals of any search and rescue operation. The aim of this paper is to address the task of automatically finding people lying on the ground in images taken from the on-board camera of an unmanned aerial vehicle (UAV). In this paper we evaluate various state-of-the-art visual people detection methods in the context of vision based victim detection from an UAV. The top performing approaches in this comparison are those that rely on flexible part-based representations and discriminatively trained part detectors. We discuss their strengths and weaknesses and demonstrate that by combining multiple models we can increase the reliability of the system. We also demonstrate that the detection performance can be substantially improved by integrating the height and pitch information provided by on-board sensors. Jointly thes

Year: 2011
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