Imperial College London
Alternate

ProfessorAndrewDavison

Faculty of Engineering, Department of Computing

Professor of Robot Vision
 
 
 
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Contact

 

+44 (0)20 7594 8316a.davison Website

 
 
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Assistant

 

Ms Lucy Atthis +44 (0)20 7594 8259

 
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Location

 

303William Penney LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Sucar:2022:10.1109/iccv48922.2021.00617,
author = {Sucar, E and Liu, S and Ortiz, J and Davison, AJ},
doi = {10.1109/iccv48922.2021.00617},
pages = {6209--6218},
publisher = {IEEE},
title = {iMAP: implicit mapping and positioning in real-time},
url = {http://dx.doi.org/10.1109/iccv48922.2021.00617},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - We show for the first time that a multilayer perceptron (MLP) can serve as the only scene representation in a real-time SLAM system for a handheld RGB-D camera. Our network is trained in live operation without prior data, building a dense, scene-specific implicit 3D model of occupancy and colour which is also immediately used for tracking.Achieving real-time SLAM via continual training of a neural network against a live image stream requires significant innovation. Our iMAP algorithm uses a keyframe structure and multi-processing computation flow, with dynamic information-guided pixel sampling for speed, with tracking at 10 Hz and global map updating at 2 Hz. The advantages of an implicit MLP over standard dense SLAM techniques include efficient geometry representation with automatic detail control and smooth, plausible filling-in of unobserved regions such as the back surfaces of objects.
AU  - Sucar,E
AU  - Liu,S
AU  - Ortiz,J
AU  - Davison,AJ
DO  - 10.1109/iccv48922.2021.00617
EP  - 6218
PB  - IEEE
PY  - 2022///
SP  - 6209
TI  - iMAP: implicit mapping and positioning in real-time
UR  - http://dx.doi.org/10.1109/iccv48922.2021.00617
UR  - https://ieeexplore.ieee.org/document/9710431
UR  - http://hdl.handle.net/10044/1/97341
ER  -
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