@article{ref1,
title="Vision-based responders localization techniques in urban search and rescue scenarios",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2016",
author="Yang, Zhuorui and Ganz, Aura and Zhuorui Yang,  and Ganz, Aura and Yang, Zhuorui and Ganz, Aura",
volume="2016",
number="",
pages="2640-2643",
abstract="In this paper, we introduce a vision-based localization algorithm that can accurately track responders during rescue operations in urban areas that are Global Navigation Satellite System (GNSS)-denied. The proposed algorithm works successfully with the rich visual features of an urban environment and obtains an average localization accuracy of 2.5 ft. In addition, we also provide a 3D representation of the disaster field which reflects the current conditions of the site.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2016.7591272",
url="http://dx.doi.org/10.1109/EMBC.2016.7591272"
}