Handa, Ankur and Whelan, Thomas and McDonald, John and Davison, Andrew J.
(2014)
A Benchmark for RGB-D Visual Odometry, 3D Reconstruction and
SLAM.
In:
IEEE International Conference on Robotics and Automation (ICRA), 2014.
IEEE, pp. 1524-1531.
ISBN 9781479936854
Abstract
We introduce the Imperial College London and
National University of Ireland Maynooth (ICL-NUIM) dataset
for the evaluation of visual odometry, 3D reconstruction and
SLAM algorithms that typically use RGB-D data. We present
a collection of handheld RGB-D camera sequences within
synthetically generated environments. RGB-D sequences with
perfect ground truth poses are provided as well as a ground
truth surface model that enables a method of quantitatively
evaluating the final map or surface reconstruction accuracy.
Care has been taken to simulate typically observed real-world
artefacts in the synthetic imagery by modelling sensor noise in
both RGB and depth data. While this dataset is useful for the
evaluation of visual odometry and SLAM trajectory estimation,
our main focus is on providing a method to benchmark the
surface reconstruction accuracy which to date has been missing
in the RGB-D community despite the plethora of ground truth
RGB-D datasets available.
| Item Type: |
Book Section
|
| Keywords: |
SLAM (robots); distance measurement; image colour analysis; image reconstruction; image sequences; |
| Academic Unit: |
Faculty of Science and Engineering > Computer Science |
| Item ID: |
8309 |
| Identification Number: |
https://doi.org/10.1109/ICRA.2014.6907054 |
| Depositing User: |
John McDonald
|
| Date Deposited: |
12 Jun 2017 14:57 |
| Journal or Publication Title: |
IEEE International Conference on Robotics and Automation (ICRA) 2014 |
| Publisher: |
IEEE |
| Refereed: |
Yes |
| Funders: |
Science Foundation Ireland, Irish Research Council |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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