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Robust monocular visual odometry by uncertainty voting

David Van Hamme UGent, Peter Veelaert UGent and Wilfried Philips UGent (2011) IEEE Intelligent Vehicles Symposium. p.643-647
abstract
GPS by itself is not dependable in urban environments, due to signal reception issues such as multi-path effects or occlusion. Other sensor data is required to keep track of the vehicle in absence of a reliable GPS signal. We propose a new method to use a single on-board consumer-grade camera for vehicle motion estimation. The method is based on the tracking of ground plane features, taking into account the uncertainty on their backprojection as well as the uncertainty on the vehicle motion. A Hough-like parameter space vote is employed to extract motion parameters from the uncertainty models. The method is easy to calibrate and designed to be robust to outliers and bad feature quality. Experimental results show good accuracy and high reliability, with a positional estimate within 2 metres for a 400 metre elapsed distance.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
image motion analysis, Hough transforms, Global Positioning System, computer vision, feature extraction, tracking, uncertainty handling
in
IEEE Intelligent Vehicles Symposium
issue title
2011 IEEE Intelligent Vehicles Symposium
pages
643 - 647
publisher
IEEE
place of publication
New York, NY, USA
conference name
2011 IEEE Intelligent Vehicles Symposium (IV 2011]
conference location
Baden-Baden, Germany
conference start
2011-06-05
conference end
2011-06-09
Web of Science type
Proceedings Paper
Web of Science id
000298736200107
ISSN
1931-0587
ISBN
9781457708916
9781457708909
DOI
10.1109/IVS.2011.5940453
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1887207
handle
http://hdl.handle.net/1854/LU-1887207
date created
2011-08-10 12:21:40
date last changed
2012-11-13 16:35:25
@inproceedings{1887207,
  abstract     = {GPS by itself is not dependable in urban environments, due to signal reception issues such as multi-path effects or occlusion. Other sensor data is required to keep track of the vehicle in absence of a reliable GPS signal. We propose a new method to use a single on-board consumer-grade camera for vehicle motion estimation. The method is based on the tracking of ground plane features, taking into account the uncertainty on their backprojection as well as the uncertainty on the vehicle motion. A Hough-like parameter space vote is employed to extract motion parameters from the uncertainty models. The method is easy to calibrate and designed to be robust to outliers and bad feature quality. Experimental results show good accuracy and high reliability, with a positional estimate within 2 metres for a 400 metre elapsed distance.},
  author       = {Van Hamme, David and Veelaert, Peter and Philips, Wilfried},
  booktitle    = {IEEE Intelligent Vehicles Symposium},
  isbn         = {9781457708916},
  issn         = {1931-0587},
  keyword      = {image motion analysis,Hough transforms,Global Positioning System,computer vision,feature extraction,tracking,uncertainty handling},
  language     = {eng},
  location     = {Baden-Baden, Germany},
  pages        = {643--647},
  publisher    = {IEEE},
  title        = {Robust monocular visual odometry by uncertainty voting},
  url          = {http://dx.doi.org/10.1109/IVS.2011.5940453},
  year         = {2011},
}

Chicago
Van Hamme, David, Peter Veelaert, and Wilfried Philips. 2011. “Robust Monocular Visual Odometry by Uncertainty Voting.” In IEEE Intelligent Vehicles Symposium, 643–647. New York, NY, USA: IEEE.
APA
Van Hamme, D., Veelaert, P., & Philips, W. (2011). Robust monocular visual odometry by uncertainty voting. IEEE Intelligent Vehicles Symposium (pp. 643–647). Presented at the 2011 IEEE Intelligent Vehicles Symposium (IV 2011], New York, NY, USA: IEEE.
Vancouver
1.
Van Hamme D, Veelaert P, Philips W. Robust monocular visual odometry by uncertainty voting. IEEE Intelligent Vehicles Symposium. New York, NY, USA: IEEE; 2011. p. 643–7.
MLA
Van Hamme, David, Peter Veelaert, and Wilfried Philips. “Robust Monocular Visual Odometry by Uncertainty Voting.” IEEE Intelligent Vehicles Symposium. New York, NY, USA: IEEE, 2011. 643–647. Print.