A framework for global vehicle localization using stereo images and satellite and road maps

Turgay Senlet, Ahmed Elgammal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Scopus citations

Abstract

We present a framework for global vehicle localization and 3D point cloud reconstruction that combines stereo visual odometry, satellite images, and road maps under a particle-filtering architecture. The framework focuses on the general vehicle localization scenario without the use of global positioning system for urban and rural environments and with the presence of moving objects. The main novelties of our approach are using road maps and rendering accurate top views using stereo reconstruction, and match these views with the satellite images in order to eliminate drifts and obtain accurate global localization. We show that our method is practicable by presenting experimental results on a 2 km road where mostly specific road features do not exist.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Pages2034-2041
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain
Duration: Nov 6 2011Nov 13 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Country/TerritorySpain
CityBarcelona
Period11/6/1111/13/11

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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