BibTex format
@inproceedings{Bujanca:2019:10.1109/icra.2019.8794369,
author = {Bujanca, M and Gafton, P and Saeedi, S and Nisbet, A and Bodin, B and O'Boyle, MFP and Davison, AJ and Paul, HJ K and Riley, G and Lennox, B and Lujan, M and Furber, S},
doi = {10.1109/icra.2019.8794369},
publisher = {Institute of Electrical and Electronics Engineers},
title = {SLAMBench 3.0: Systematic automated reproducible evaluation of SLAM systems for robot vision challenges and scene understanding},
url = {http://dx.doi.org/10.1109/icra.2019.8794369},
year = {2019}
}
RIS format (EndNote, RefMan)
TY - CPAPER
AB - As the SLAM research area matures and the number of SLAM systems available increases, the need for frameworks that can objectively evaluate them against prior work grows. This new version of SLAMBench moves beyond traditional visual SLAM, and provides new support for scene understanding and non-rigid environments (dynamic SLAM). More concretely for dynamic SLAM, SLAMBench 3.0 includes the first publicly available implementation of DynamicFusion, along with an evaluation infrastructure. In addition, we include two SLAM systems (one dense, one sparse) augmented with convolutional neural networks for scene understanding, together with datasets and appropriate metrics. Through a series of use-cases, we demonstrate the newly incorporated algorithms, visulation aids and metrics (6 new metrics, 4 new datasets and 5 new algorithms).
AU - Bujanca,M
AU - Gafton,P
AU - Saeedi,S
AU - Nisbet,A
AU - Bodin,B
AU - O'Boyle,MFP
AU - Davison,AJ
AU - Paul,HJ K
AU - Riley,G
AU - Lennox,B
AU - Lujan,M
AU - Furber,S
DO - 10.1109/icra.2019.8794369
PB - Institute of Electrical and Electronics Engineers
PY - 2019///
SN - 1050-4729
TI - SLAMBench 3.0: Systematic automated reproducible evaluation of SLAM systems for robot vision challenges and scene understanding
UR - http://dx.doi.org/10.1109/icra.2019.8794369
UR - http://hdl.handle.net/10044/1/73402
ER -
