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{Wada:2020:10.1109/cvpr42600.2020.01455,
author = {Wada, K and Sucar, E and James, S and Lenton, D and Davison, AJ},
doi = {10.1109/cvpr42600.2020.01455},
publisher = {IEEE},
title = {MoreFusion: multi-object reasoning for 6D pose estimation from volumetric fusion},
url = {http://dx.doi.org/10.1109/cvpr42600.2020.01455},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Robots and other smart devices need efficient object-based scene representations from their on-board vision systems to reason about contact, physics and occlusion. Recognized precise object models will play an important role alongside non-parametric reconstructions of unrecognized structures. We present a system which can estimate the accurate poses of multiple known objects in contact and occlusion from real-time, embodied multi-view vision. Our approach makes 3D object pose proposals from single RGB-D views, accumulates pose estimates and non-parametric occupancy information from multiple views as the camera moves, and performs joint optimization to estimate consistent, non-intersecting poses for multiple objects in contact. We verify the accuracy and robustness of our approach experimentally on 2 object datasets: YCB-Video, and our own challenging Cluttered YCB-Video. We demonstrate a real-time robotics application where a robot arm precisely and orderly disassembles complicated piles of objects, using only on-board RGB-D vision.
AU  - Wada,K
AU  - Sucar,E
AU  - James,S
AU  - Lenton,D
AU  - Davison,AJ
DO  - 10.1109/cvpr42600.2020.01455
PB  - IEEE
PY  - 2020///
TI  - MoreFusion: multi-object reasoning for 6D pose estimation from volumetric fusion
UR  - http://dx.doi.org/10.1109/cvpr42600.2020.01455
UR  - https://ieeexplore.ieee.org/document/9157179
ER  -
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