ML Anthology

Localization in Urban Environments: Monocular Vision Compared to a Differential GPS Sensor

Eric Royer, Maxime Lhuillier, Michel Dhome, Thierry Chateau
CVPR 2005 pp. 114-121
doi:10.1109/CVPR.2005.217 /cvpr/2005/royer2005cvpr-localization/

Abstract

In this paper we present a method for computing the localization of a mobile robot with reference to a learning video sequence. The robot is first guided on a path by a human, while the camera records a monocular learning sequence. Then a 3D reconstruction of the path and the environment is computed off line from the learning sequence. The 3D reconstruction is then used for computing the pose of the robot in real time (30 Hz) in autonomous navigation. Results from our localization method are compared to the ground truth measured with a differential GPS.

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Text

Royer et al. "Localization in Urban Environments: Monocular Vision Compared to a Differential GPS Sensor." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.217

Markdown

[Royer et al. "Localization in Urban Environments: Monocular Vision Compared to a Differential GPS Sensor." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/royer2005cvpr-localization/) doi:10.1109/CVPR.2005.217

BibTeX

@inproceedings{royer2005cvpr-localization,
  title     = {{Localization in Urban Environments: Monocular Vision Compared to a Differential GPS Sensor}},
  author    = {Royer, Eric and Lhuillier, Maxime and Dhome, Michel and Chateau, Thierry},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2005},
  pages     = {114-121},
  doi       = {10.1109/CVPR.2005.217},
  url       = {https://mlanthology.org/cvpr/2005/royer2005cvpr-localization/}
}