In this section
@inproceedings{Saputra:2018:10.1007/978-3-319-96728-8,
author = {Saputra, RP and Kormushev, P},
doi = {10.1007/978-3-319-96728-8},
pages = {473--475},
publisher = {Springer, Cham},
title = {Casualty detection for mobile rescue robots via ground-projected point clouds},
url = {http://dx.doi.org/10.1007/978-3-319-96728-8},
year = {2018}
}
TY - CPAPER
AB - In order to operate autonomously, mobile rescue robots needto be able to detect human casualties in disaster situations. In this paper,we propose a novel method for autonomous detection of casualties lyingdown on the ground based on point-cloud data. This data can be obtainedfrom different sensors, such as an RGB-D camera or a 3D LIDAR sensor.The method is based on a ground-projected point-cloud (GPPC) imageto achieve human body shape detection. A preliminary experiment hasbeen conducted using the RANSAC method for floor detection and, theHOG feature and the SVM classifier to detect human body shape. Theresults show that the proposed method succeeds to identify a casualtyfrom point-cloud data in a wide range of viewing angles.
AU - Saputra,RP
AU - Kormushev,P
DO - 10.1007/978-3-319-96728-8
EP - 475
PB - Springer, Cham
PY - 2018///
SN - 0302-9743
SP - 473
TI - Casualty detection for mobile rescue robots via ground-projected point clouds
UR - http://dx.doi.org/10.1007/978-3-319-96728-8
UR - http://hdl.handle.net/10044/1/62803
ER -
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