Metric localization using Google Street View

  title={Metric localization using Google Street View},
  author={Pratik Agarwal and Wolfram Burgard and Luciano Spinello},
  journal={2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
Accurate metrical localization is one of the central challenges in mobile robotics. Many existing methods aim at localizing after building a map with the robot. In this paper, we present a novel approach that instead uses geo-tagged panoramas from the Google Street View as a source of global positioning. We model the problem of localization as a non-linear least squares estimation in two phases. The first estimates the 3D position of tracked feature points from short monocular camera sequences… CONTINUE READING
Highly Cited
This paper has 68 citations. REVIEW CITATIONS
Related Discussions
This paper has been referenced on Twitter 6 times. VIEW TWEETS


Publications citing this paper.
Showing 1-10 of 26 extracted citations

Global localization of 3D point clouds in building outline maps of urban outdoor environments

International Journal of Intelligent Robotics and Applications • 2017
View 10 Excerpts
Highly Influenced


E. Boussias-Alexakis, V. Tsironis, E. Petsa, George. Karras
View 6 Excerpts
Highly Influenced

Compensating drift of mono-visual odometry using road direction sign database

2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) • 2017
View 1 Excerpt

69 Citations

Citations per Year
Semantic Scholar estimates that this publication has 69 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 28 references

AprilTag: A robust and flexible visual fiducial system

2011 IEEE International Conference on Robotics and Automation • 2011
View 4 Excerpts
Highly Influenced

Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision • 2004
View 3 Excerpts
Highly Influenced

Robust Graph-Based Localization and Mapping

P. Agarwal
PhD thesis, • 2015
View 1 Excerpt

Incremental smoothing and mapping using the Bayes tree

H. Johannsson M. Kaess, R. Roberts, V.. Ila, J. J. Leonard, F. Dellaert
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition ( CVPR ) • 2013

MAV urban localization from Google street view data

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems • 2013
View 1 Excerpt

Street View Motion-from-Structure-from-Motion

2013 IEEE International Conference on Computer Vision • 2013
View 2 Excerpts

Fast Matching of Binary Features

2012 Ninth Conference on Computer and Robot Vision • 2012
View 2 Excerpts