Imperial College London
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DrStefanLeutenegger

Faculty of Engineering, Department of Computing

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Contact

 

s.leutenegger Website

 
 
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Location

 

ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Landgraf:2020,
author = {Landgraf, Z and Falck, F and Bloesch, M and Leutenegger, S and Davison, A},
publisher = {arXiv},
title = {Comparing view-based and map-based semantic labelling in real-time SLAM},
url = {http://arxiv.org/abs/2002.10342v1},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - Generally capable Spatial AI systems must build persistent scenerepresentations where geometric models are combined with meaningful semanticlabels. The many approaches to labelling scenes can be divided into two cleargroups: view-based which estimate labels from the input view-wise data and thenincrementally fuse them into the scene model as it is built; and map-basedwhich label the generated scene model. However, there has so far been noattempt to quantitatively compare view-based and map-based labelling. Here, wepresent an experimental framework and comparison which uses real-time heightmap fusion as an accessible platform for a fair comparison, opening up theroute to further systematic research in this area.
AU  - Landgraf,Z
AU  - Falck,F
AU  - Bloesch,M
AU  - Leutenegger,S
AU  - Davison,A
PB  - arXiv
PY  - 2020///
TI  - Comparing view-based and map-based semantic labelling in real-time SLAM
UR  - http://arxiv.org/abs/2002.10342v1
UR  - http://hdl.handle.net/10044/1/79817
ER  -
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