Citation

Yang Z, Ganz A, Zhuorui Yang, Ganz A, Yang Z, Ganz A. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2016; 2016: 2640-2643.

Copyright

(Copyright © 2016, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/EMBC.2016.7591272

PMID

28227062

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.

Language: en